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Pp Beehiiv

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mvanhorn
pp-beehiiv

Sync your Beehiiv audience to a local database and answer growth questions offline in one command. Trigger phrases: `check my beehiiv growth`, `subscriber sources`, `which send time works best`, `compare my publications`, `lookup subscriber email`, `use beehiiv`, `run beehiiv`.

Overview

Publishermvanhorn
Repositoryprinting-press-library
Skill namepp-beehiiv
Stars
2K
Forks
614
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by mvanhorn on GitHub. Read the source before you install it.

Installation

Install the Pp Beehiiv AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mvanhorn/printing-press-library.git /tmp/printing-press-library
mkdir -p .claude/skills
cp -r /tmp/printing-press-library/cli-skills/pp-beehiiv .claude/skills/pp-beehiiv
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pp Beehiiv in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pp Beehiiv on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pp Beehiiv is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Beehiiv — Printing Press CLI

Prerequisites: Install the CLI

This skill drives the beehiiv-pp-cli binary. You must verify the CLI is installed before invoking any command from this skill. If it is missing, install it first:

  1. Install via the Printing Press installer. It defaults binaries to $HOME/.local/bin on macOS/Linux and %LOCALAPPDATA%\Programs\PrintingPress\bin on Windows:
    bash
    npx -y @mvanhorn/printing-press-library install beehiiv --cli-only
  2. Verify: beehiiv-pp-cli --version
  3. Ensure the reported install directory is on $PATH for the agent/runtime that will invoke this skill.

If the npx install fails (no Node, offline, etc.), fall back to a direct Go install (requires Go 1.26.6 or newer). This installs into $GOPATH/bin (default $HOME/go/bin), so add that directory to $PATH instead:

bash
go install github.com/mvanhorn/printing-press-library/library/marketing/beehiiv/cmd/beehiiv-pp-cli@latest

If --version reports "command not found" after install, the runtime cannot see the binary directory on $PATH. Do not proceed with skill commands until verification succeeds.

Beehiiv-pp-cli mirrors publications, subscribers, segments, posts, podcasts, and more into SQLite. Insights commands compute source attribution, churn sources, send-time performance, and cross-publication comparisons with zero API calls. The full v2 surface, including 2026-09 additions like podcasts, exports, and complimentary access, ships as typed commands with dry-run and agent output.

When to Use This CLI

Use this CLI for offline audience analytics, bulk subscriber operations, scripting, and CI pipelines. Use it when you want agent-ready JSON output with select/compact/quiet modes and a local store that answers growth questions without API calls.

Anti-triggers

Do not use this CLI for:

  • Do not use this CLI for beehiv documentation search; use the official docs MCP at developers.beehiiv.com/_mcp/server
  • Do not use this CLI for OAuth app authorization flows; it is an API-key client
  • Creating a post with confirmed status and no scheduled_at publishes (sends) immediately; use --dry-run first to inspect the request

Unique Capabilities

These capabilities aren't available in any other tool for this API.

Growth answers from the local store

  • insights subscriber-sources — See exactly where new subscribers come from: UTM, channel, and referring site, grouped in one call.

    Reach for this when a growth question needs source attribution without paging the full subscriber list through the API.

    bash
    beehiiv-pp-cli insights subscriber-sources pub_477b0b68-0ab1-4b3f-954e-d1f6302b58a7 --limit 20 --agent
  • insights post-performance — Review recent sends with status, timing, and expanded stats in one compact table.

    Reach for this after a send to review performance without burning per-post API calls.

    bash
    beehiiv-pp-cli insights post-performance pub_477b0b68-0ab1-4b3f-954e-d1f6302b58a7 --limit 10 --agent
  • insights referral-health — Check referral-program config and how many subscribers actually carry referral codes.

    Reach for this when tuning referral loops to see configuration versus real coverage.

    bash
    beehiiv-pp-cli insights referral-health pub_477b0b68-0ab1-4b3f-954e-d1f6302b58a7 --agent
  • insights subscriber-lookup — Find one subscriber by email or subscription ID and get a compact record instantly.

    Reach for this for support questions about a single subscriber when offline speed matters.

    bash
    beehiiv-pp-cli insights subscriber-lookup pub_477b0b68-0ab1-4b3f-954e-d1f6302b58a7 reader@example.com --agent --select subscription.email,subscription.status
  • insights churn-sources — See which sources, channels, and campaigns drive unsubscribes.

    Reach for this when unsubscribes spike and you need the offending channel fast.

    bash
    beehiiv-pp-cli insights churn-sources pub_477b0b68-0ab1-4b3f-954e-d1f6302b58a7 --limit 20 --agent
  • insights send-times — Find your best send slot: open rate by weekday and hour from your own history.

    Reach for this when scheduling the next send and you want evidence over habit.

    bash
    beehiiv-pp-cli insights send-times pub_477b0b68-0ab1-4b3f-954e-d1f6302b58a7 --agent
  • insights compare-publications — Side-by-side growth and engagement across every synced publication.

    Reach for this when managing several publications and a client report needs one comparison table.

    bash
    beehiiv-pp-cli insights compare-publications --agent --select publications.name,publications.net_growth

Command Reference

advertisement-opportunities — Manage advertisement opportunities

  • beehiiv-pp-cli advertisement-opportunities <publicationId> — Get advertisement opportunities OAuth Scope: posts:read

authors — Manage authors

  • beehiiv-pp-cli authors index — Retrieve a list of authors available for the publication.
  • beehiiv-pp-cli authors show — Retrieve a single author from a publication.

automations — Manage automations

  • beehiiv-pp-cli automations index — List automations OAuth Scope: automations:read
  • beehiiv-pp-cli automations show — Get automation OAuth Scope: automations:read

bulk-subscription-updates — Manage bulk subscription updates

  • beehiiv-pp-cli bulk-subscription-updates index — List subscription updates OAuth Scope: subscriptions:read
  • beehiiv-pp-cli bulk-subscription-updates show — Get subscription update OAuth Scope: subscriptions:read

bulk-subscriptions — Manage bulk subscriptions

  • beehiiv-pp-cli bulk-subscriptions <publicationId> — Bulk create subscription OAuth Scope: subscriptions:write

complimentary-access — Manage complimentary access

  • beehiiv-pp-cli complimentary-access index — Retrieve complimentary access objects for the publication.
  • beehiiv-pp-cli complimentary-access show — Retrieve a single complimentary access object.

condition-sets — Manage condition sets

  • beehiiv-pp-cli condition-sets index — Retrieve all active condition sets for a publication.
  • beehiiv-pp-cli condition-sets show — Retrieve a single active dynamic content condition set for a publication.

custom-fields — Manage custom fields

  • beehiiv-pp-cli custom-fields create — Create custom field OAuth Scope: custom_fields:write
  • beehiiv-pp-cli custom-fields delete — Delete custom field OAuth Scope: custom_fields:write
  • beehiiv-pp-cli custom-fields index — List custom fields OAuth Scope: custom_fields:read
  • beehiiv-pp-cli custom-fields patch — Update custom field OAuth Scope: custom_fields:write
  • beehiiv-pp-cli custom-fields put — Update custom field OAuth Scope: custom_fields:write
  • beehiiv-pp-cli custom-fields show — Get custom field OAuth Scope: custom_fields:read

data-privacy — Manage data privacy

  • beehiiv-pp-cli data-privacy data-deletion-createThis is a gated feature that requires enablement.
  • beehiiv-pp-cli data-privacy data-deletion-indexThis is a gated feature that requires enablement.
  • beehiiv-pp-cli data-privacy data-deletion-showThis is a gated feature that requires enablement.

email-blasts — Manage email blasts

  • beehiiv-pp-cli email-blasts index — List email blasts OAuth Scope: posts:read
  • beehiiv-pp-cli email-blasts show — Get email blast OAuth Scope: posts:read

engagements — Manage engagements

  • beehiiv-pp-cli engagements <publicationId> — Retrieve email engagement metrics for a specific publication over a defined date range and granularity.

exports — Manage exports

  • beehiiv-pp-cli exports subscription-create — Start a subscription export. Returns an existing in-progress export instead of starting a duplicate.
  • beehiiv-pp-cli exports subscription-index — List subscription exports for the publication, newest first.
  • beehiiv-pp-cli exports subscription-show — Get a subscription export. Poll until status is completed, then read download_url. Gated feature requiring enablement.

newsletter-lists — Manage newsletter lists

  • beehiiv-pp-cli newsletter-lists index Newsletter Lists is currently in beta, the API is subject to change.
  • beehiiv-pp-cli newsletter-lists show Newsletter Lists is currently in beta, the API is subject to change.

podcasts — Manage podcasts

  • beehiiv-pp-cli podcasts index — List podcasts for the publication.
  • beehiiv-pp-cli podcasts show — Retrieve a single podcast.

polls — Manage polls

  • beehiiv-pp-cli polls index — Retrieve all polls belonging to a specific publication. Poll choices are always included.
  • beehiiv-pp-cli polls show — Retrieve detailed information about a specific poll belonging to a publication.

post-templates — Manage post templates

  • beehiiv-pp-cli post-templates <publicationId> — Retrieve a list of post templates available for the publication.

posts — Manage posts

  • beehiiv-pp-cli posts aggregate-stats — Get aggregate stats OAuth Scope: posts:read
  • beehiiv-pp-cli posts create This feature is currently in beta, the API is subject to change
  • beehiiv-pp-cli posts delete — Delete or Archive a post. Any post that has been confirmed will have it's status changed to archived.
  • beehiiv-pp-cli posts index — List posts OAuth Scope: posts:read
  • beehiiv-pp-cli posts show — Get post OAuth Scope: posts:read
  • beehiiv-pp-cli posts update This feature is currently in beta, the API is subject to change

publications — Manage publications

  • beehiiv-pp-cli publications index — List publications OAuth Scope: publications:read
  • beehiiv-pp-cli publications show — Get publication OAuth Scope: publications:read

referral-program — Manage referral program

  • beehiiv-pp-cli referral-program <publicationId> — Get referral program OAuth Scope: referral_program:read

segments — Manage segments

  • beehiiv-pp-cli segments create — Create a new segment.
  • beehiiv-pp-cli segments delete — Delete a segment. Deleting the segment does not effect the subscriptions in the segment.
  • beehiiv-pp-cli segments index — List segments OAuth Scope: segments:read
  • beehiiv-pp-cli segments show — Get segment OAuth Scope: segments:read

subscriptions — Manage subscriptions

  • beehiiv-pp-cli subscriptions bulk-updates-patch — Update subscriptions OAuth Scope: subscriptions:write
  • beehiiv-pp-cli subscriptions bulk-updates-patch-status — Update subscriptions' status OAuth Scope: subscriptions:write
  • beehiiv-pp-cli subscriptions bulk-updates-put — Update subscriptions OAuth Scope: subscriptions:write
  • beehiiv-pp-cli subscriptions bulk-updates-put-status — Update subscriptions' status OAuth Scope: subscriptions:write
  • beehiiv-pp-cli subscriptions create — Create subscription OAuth Scope: subscriptions:write
  • beehiiv-pp-cli subscriptions deleteThis cannot be undone. All data associated with the subscription will also be deleted.
  • beehiiv-pp-cli subscriptions get-by-emailPlease note that this endpoint requires the email to be URL encoded.
  • beehiiv-pp-cli subscriptions get-by-idIn previous versions of the API, another endpoint existed to retrieve a subscription by the subscriber ID.
  • beehiiv-pp-cli subscriptions get-by-subscriber-id — Get subscription by subscriber ID OAuth Scope: subscriptions:read
  • beehiiv-pp-cli subscriptions index — Retrieve all subscriptions belonging to a specific publication.
  • beehiiv-pp-cli subscriptions patch — Update subscription by ID OAuth Scope: subscriptions:write
  • beehiiv-pp-cli subscriptions put — Update subscription by ID OAuth Scope: subscriptions:write
  • beehiiv-pp-cli subscriptions update-by-email — Update subscription by email OAuth Scope: subscriptions:write

tiers — Manage tiers

  • beehiiv-pp-cli tiers create — Create a tier OAuth Scope: tiers:write
  • beehiiv-pp-cli tiers index — List tiers OAuth Scope: tiers:read
  • beehiiv-pp-cli tiers patch — Update a tier OAuth Scope: tiers:write
  • beehiiv-pp-cli tiers put — Update a tier OAuth Scope: tiers:write
  • beehiiv-pp-cli tiers show — Get tier OAuth Scope: tiers:read

users — Manage users

  • beehiiv-pp-cli users — Identify user OAuth Scope: identify:read

webhooks — Manage webhooks

  • beehiiv-pp-cli webhooks create — Create a webhook OAuth Scope: webhooks:write
  • beehiiv-pp-cli webhooks delete — Delete a webhook OAuth Scope: webhooks:write
  • beehiiv-pp-cli webhooks index — List webhooks OAuth Scope: webhooks:read
  • beehiiv-pp-cli webhooks show — Get webhook OAuth Scope: webhooks:read
  • beehiiv-pp-cli webhooks update — Update webhook OAuth Scope: webhooks:write

workspaces — Manage workspaces

  • beehiiv-pp-cli workspaces identify — Identify workspace OAuth Scope: identify:read
  • beehiiv-pp-cli workspaces permissions-show — Retrieve the permissions granted to the OAuth or API token for this workspace.
  • beehiiv-pp-cli workspaces publications-by-subscription-email — Retrieve all publications in the workspace that have a subscription for the specified email address.

Finding the right command

When you know what you want to do but not which command does it, ask the CLI directly:

bash
beehiiv-pp-cli which "<capability in your own words>"

which resolves a natural-language capability query to the best matching command from this CLI's curated feature index. Exit code 0 means at least one match; exit code 2 means no confident match — fall back to --help or use a narrower query.

Recipes

Mirror the audience

bash
beehiiv-pp-cli sync --resources publications,subscriptions,segments,posts --max-pages 100

Cursor-paginated sync of the four growth-critical entities into SQLite.

Agent-ready growth snapshot

bash
beehiiv-pp-cli insights growth-summary pub_477b0b68-0ab1-4b3f-954e-d1f6302b58a7 --agent

Single read-only health summary computed from the local store.

Narrow a deep lookup

bash
beehiiv-pp-cli insights subscriber-lookup pub_477b0b68-0ab1-4b3f-954e-d1f6302b58a7 reader@example.com --agent --select subscription.email,subscription.status

Pair --agent with --select dotted paths to return only the fields an agent needs.

Attribute a churn spike

bash
beehiiv-pp-cli insights churn-sources pub_477b0b68-0ab1-4b3f-954e-d1f6302b58a7 --limit 20

Group unsubscribes by source, channel, UTM, and referrer offline.

Ship a subscriber CSV

bash
beehiiv-pp-cli search "@example.com" --type subscriptions --limit 1000 --csv > subscribers.csv

Every list and search command emits CSV for spreadsheets.

Auth Setup

Create an API key at app.beehiiv.com (Settings > API Keys) and export BEEHIIV_API_KEY. The key is a bearer token scoped to your organization; 180 requests per minute are shared per org.

Run beehiiv-pp-cli doctor to verify setup.

Agent Mode

Add --agent to any command. Expands to: --json --compact --no-input --no-color.

  • Pipeable — JSON on stdout, errors on stderr

  • Filterable--select keeps a subset of fields. Dotted paths descend into nested structures; arrays traverse element-wise. Critical for keeping context small on verbose APIs:

    bash
    beehiiv-pp-cli advertisement-opportunities mock-value --agent --select advertisement_kind,advertiser_name,id
  • Previewable--dry-run shows the request without sending

  • Offline-friendly — sync/search commands can use the local SQLite store when available

  • Non-interactive — never prompts, every input is a flag

  • Explicit confirmation--agent does not imply --yes; pass --yes separately only after the target, arguments, and side effects are clear

  • Explicit retries — use --idempotent only when an already-existing create should count as success, and use --ignore-missing only when a missing delete target should count as success

Response envelope

Commands that read from the local store or the API wrap output in a provenance envelope:

json
{
  "meta": {"source": "live" | "local", "synced_at": "...", "reason": "..."},
  "results": <data>
}

Parse .results for data and .meta.source to know whether it's live or local. A human-readable N results (live) summary is printed to stderr only when stdout is a terminal AND no machine-format flag (--json, --csv, --compact, --quiet, --plain, --select) is set — piped/agent consumers and explicit-format runs get pure JSON on stdout.

Paths and state

Agents should treat the CLI's path resolver as part of the runtime contract:

  • Use --home <dir> for one invocation, or set BEEHIIV_HOME=<dir> to relocate all four path kinds under one root.

  • Use per-kind env vars only when a specific kind must diverge: BEEHIIV_CONFIG_DIR, BEEHIIV_DATA_DIR, BEEHIIV_STATE_DIR, BEEHIIV_CACHE_DIR.

  • Resolution order is per-kind env var, --home, BEEHIIV_HOME, XDG (XDG_CONFIG_HOME, XDG_DATA_HOME, XDG_STATE_HOME, XDG_CACHE_HOME), then platform defaults.

  • config contains settings like config.toml and profiles. data contains credentials.toml, data.db, cookies, and auth sidecars. state contains persisted queries, jobs, and teach.log. cache contains regenerable HTTP/cache files.

  • Stored secrets live in credentials.toml under the data dir. Existing legacy config.toml secrets are read for compatibility and leave config.toml on the first auth write.

  • Run beehiiv-pp-cli doctor --fail-on warn to surface path and credential-location warnings. agent-context exposes a schema v4 paths block for agents that need the resolved dirs.

  • For MCP, pass relocation through the MCP host config. The MCP binary does not inherit CLI flags:

    json
    {
      "mcpServers": {
        "beehiiv": {
          "command": "beehiiv-pp-mcp",
          "env": {
            "BEEHIIV_HOME": "/srv/beehiiv"
          }
        }
      }
    }

Fleet precedence: an inherited per-kind env var overrides an explicit --home for that kind. Use BEEHIIV_HOME or per-kind vars as durable fleet levers, and use --home only for a single invocation. Relocation is not reversible by unsetting env vars; move files manually before clearing BEEHIIV_HOME, or doctor will not find credentials left under the former root.

Automatic learning

This CLI ships a self-capturing learning loop. The CLI does its own bookkeeping: every invocation is journaled locally, a failed flag followed by a corrected retry auto-derives a flag_alias candidate, and a teach on a query family without a playbook auto-synthesizes a playbook_candidate from the session's journal. Your job is judgment only: recall first, act on surfaced candidates, teach the final answer, playbook amend when you observe a correction. You never record failures by hand.

Step 1: recall before any discovery

Before list/search/drill commands on a new user question, run:

bash
beehiiv-pp-cli recall "<user's question>" --agent

The response envelope:

json
{
  "query": "...",
  "normalized": "<normalized form>",
  "query_entities": ["..."],
  "found": true | false,
  "match_score": 0.0,
  "results": [
    { "resource_id": "...", "resource_type": "...", "venue": "...",
      "confidence": 2, "entity_match": "exact|partial|unknown",
      "source": "taught|preseed|pattern", "warnings": ["..."] }
  ],
  "mismatches": [ /* only when --debug-mismatches */ ],
  "warnings": [ /* top-level */ ],
  "candidates": [
    { "id": 12, "class": "flag_alias | playbook_candidate",
      "summary": "...", "sightings": 3, "last_seen": "...",
      "rationale": "...",
      "next_action": ["<trial command>", "beehiiv-pp-cli learnings confirm 12"] }
  ],
  "playbook": {
    "query_family": "...",
    "playbook": {
      "steps": [ { "cmd": "<command with {slot} substitution>", "purpose": "..." } ],
      "entity_slots": ["$ENTITY"],
      "expected_tool_calls": 3
    },
    "slots_resolved": { "$ENTITY": { "token": "<live token>", "canonical": "<canonical>" } },
    "notes": "<workarounds + gotchas for this query family>"
  },
  "notes": "<duplicate surface for non-playbook callers>"
}

Empty-store short-circuit: if the store has no learnings, playbooks, or candidates yet (recall finds nothing and learnings list and learnings candidates are both empty), skip recall for the rest of this session instead of taxing every query; resume recall-first once something has been taught.

Step 2: decision tree

Read candidates, playbook, notes, results[0], and warnings in that order:

if Candidates present (warnings include "candidates_present"):
    -> candidates are try-then-confirm, never facts. Follow each candidate's
       two-step next_action verbatim: run the trial command first, then run
       `learnings confirm <id>` only after the trial verified the behavior.
       Reject a wrong candidate with `learnings reject <id>`.
    -> NEVER re-teach something recall surfaced as a candidate; confirm or
       reject that candidate instead of teaching a duplicate.
    -> candidates ride alongside playbooks and resource hits, not instead of
       them; continue with the branches below after acting on them.

if Playbook present:
    -> READ Playbook.notes verbatim FIRST (workarounds + gotchas the CLI surface doesn't expose)
    -> replay Playbook.steps in order, substituting Playbook.slots_resolved entries
       for the entity slot tokens. If a step's slot is unresolved, fall back to
       discovery for that step only.
    -> the Playbook's expected_tool_calls is a budget; if you find yourself running
       materially more, record the divergence via `beehiiv-pp-cli playbook amend`
       at end-of-session.

elif Notes present (no Playbook):
    -> read Notes verbatim before any discovery step; they carry known gotchas
       for this query family even when no structured choreography exists yet.

elif Found AND Results[0].EntityMatch == "exact" AND Results[0].Confidence >= 2:
    -> skip discovery; fetch live data for Results[*].ResourceID in parallel

elif Found AND Results[0].EntityMatch == "partial":
    -> candidate hint, NOT a hit; read the resource title to validate before trusting

elif (any row in Mismatches[] when --debug-mismatches was passed):
    -> treat as cold start; the stored learning is for a different entity
       (different canonical resolved from query_entities)

else:  // Found == false, no playbook, no notes
    -> cold start; run discovery normally; teach the answer afterward (Step 4).
       If the family has no playbook yet, that teach auto-synthesizes a
       playbook candidate from this session's journal - you do not need to
       record one by hand.

Playbook and Notes are orthogonal to the per-resource path. A recall response can carry both a Playbook AND a Results[] hit - use both: the Playbook tells you which choreography to run; the resource hits short-circuit specific steps. Default to skipping mismatches; pass --debug-mismatches only when investigating cold-start surprises.

Candidate judgment details: learnings confirm <id> prints the candidate's full payload before materializing it - check that the printed payload matches the behavior you verified. learnings reject <id> tombstones the derivation signature so the same candidate does not resurface. The envelope carries only the few candidates worth acting on now; beehiiv-pp-cli learnings candidates lists the full open set.

Graceful degradation: if learnings confirm is an unknown command, you are driving an older binary - ignore the candidates guidance and follow the rest of the protocol.

Step 3: always read warnings

  • low_confidence: row exists at confidence<2. Treat as a hint, not a skip-discovery hit.
  • resource_not_in_store: the local store doesn't have the resource the learning points at. The match validator couldn't classify entities — direct-fetch and re-evaluate.
  • cross_alias_match (per-result): the row was taught under a different alias and matched the live query's canonical via entity_lookups (e.g., a "USA" teach satisfying a "United States" recall). Trust the resource_id.
  • similar_shape_different_entity:<canonical> (top-level): a structurally matching row exists but its canonical entity differs from the live query's. Treated as cold start; the warning carries the conflicting canonical as a hint, but the row is NOT promoted into Results.
  • ambiguous_alias (top-level): a single query entity resolved to multiple canonicals (e.g., "Cards" → Arizona Cardinals + St. Louis Cardinals). Surface the ambiguity from context before committing to a resource.
  • candidates_present (top-level): the envelope carries a candidates section. Handle it via the candidates branch in Step 2 before anything else.
  • lookup_refresh_available (top-level): an entity in the query has no lookup row yet, but synced data could provide one. Run beehiiv-pp-cli sync to refresh entity lookups.
  • Top-level no_learnings_for_query_family: the table had no rows above the Jaccard floor. Pure cold start.

Step 4: teach & after finalizing your response - always

Teaching is unconditional. After resolving a query the store could not answer, background-teach the final resource mapping - no call-count threshold, no judging whether it was "worth" learning. The teach is the anchor of the loop: it triggers playbook synthesis for a family without a playbook, and same-referent phrasings fold into one family so near-duplicate teaches do not fragment the store. Fire it after assembling your user-facing response but BEFORE emitting it, with a shell & so the call returns immediately:

bash
beehiiv-pp-cli teach --query "<user's question>" --resource-type <type> --resource <id1> --resource <id2>
# (append shell `&` to background it)

Silent on success. Errors only land in teach.log under the resolved state dir. Teach the most specific resource - if the user asked a broad question and you walked through parent records to find the specific answer, teach the leaf id, not the parent. The CLI uses seeded entity_lookups for cross-alias resolution at recall time, so a teach under one alias (e.g., "Niners") satisfies future queries under another alias (e.g., "49ers", "San Francisco") automatically.

PII rule: teach the structural question with identifiers stripped - never include names, emails, phone numbers, account ids, or other personal identifiers in taught queries or notes. The CLI scans teach queries for obvious email/phone shapes and warns, but does not block; strip before teaching rather than relying on the warning.

Step 5: playbooks - optional flags, automatic synthesis

You do not need to decide whether a session "deserves" a playbook: a teach on a family without one auto-synthesizes a playbook_candidate from the session's journal, and the next session judges it via confirm/reject. Attach explicit playbook flags only when you already hold choreography worth recording verbatim - workarounds the CLI didn't surface (silently-dropped flags, undocumented params, pagination tricks, payload gotchas). Prefer the integrated one-call form - record the resource learning and the playbook in the same teach invocation:

bash
# Common case: record both the resource learning AND the playbook in one call.
beehiiv-pp-cli teach \
  --query "<user's question>" \
  --resource <id> \
  --playbook-file ~/playbooks/<shape>.json \
  --playbook-notes-file ~/playbooks/<shape>-notes.md
# (append shell `&` to background it)

# Alternate: playbook-only (no resource to record alongside).
beehiiv-pp-cli teach-playbook \
  --query "<user's question>" \
  --playbook-file ~/playbooks/<shape>.json \
  --notes-file ~/playbooks/<shape>-notes.md

Playbook files are JSON with steps, entity_slots, expected_tool_calls. Notes files are markdown carrying the gotchas verbatim. File-free callers (MCP-only agents) pass the same content inline: --playbook-json and --playbook-notes on the integrated teach form, --playbook-json and --notes on teach-playbook. On the integrated teach form, the playbook flags are optional - omit them entirely for a resource-only teach. On the standalone teach-playbook form, at least one of the playbook and notes flags must be set; both empty is rejected. Playbooks are keyed on the structural query family (entities stripped) so a recipe taught from one entity-shaped query applies to every other query of the same shape, with slots_resolved binding the live query's canonical at recall time.

When you DO find a playbook on a future recall, treat it as ground truth: replay the steps with slots_resolved substitutions, skip the discovery that the choreography already documents, and read notes before any step.

Step 6: playbook amend & when your debug response identifies a correction

If your debug-protocol response identifies a concrete correction the notes or playbook should know — a workaround, an undocumented endpoint shape, a stale field name, observed schema drift, an empty-payload fallback — fire playbook amend BEFORE emitting your user-facing response. Same fire-and-forget posture as teach.

bash
beehiiv-pp-cli playbook amend \
  --query "<exact recall query string>" \
  --add-note "<your concrete correction>"
# (append shell `&` to background it)

What counts as worth amending: a behavior you OBSERVED this session that future-you would benefit from knowing. Examples worth amending:

  • A workaround for a CLI surface that silently drops or misorders a flag.
  • An undocumented endpoint shape (response wrapped in {meta, results}, payload nested two levels deeper than the docs claim).
  • Observed schema drift (a field renamed, an index that shifted between seasons, a category label that the API now returns lower-cased).

What does NOT belong in notes:

  • The year-specific or entity-specific answer to the user's question. That's the response, not a learning.
  • Per-team / per-athlete / per-row data the playbook already retrieves at runtime.
  • Statements that paraphrase what the existing notes already say.

The amend command appends to the family's existing notes with a timestamped marker ([amend YYYY-MM-DDTHH:MMZ]: <text>). Multiple amends accumulate; the audit trail is visible. If no playbook exists yet for the family, amend creates a notes-only one (so cold-start corrections still land).

PII discipline for amend notes

playbook amend notes are designed to potentially flow upstream as shared knowledge in future versions of the Printing Press. Keep them clean of user-identifying content so the upstream-contribution path stays open without retroactive scrubbing:

  • Do NOT embed paths to user filesystems, personal API keys or tokens, user email addresses, user GitHub handles, or specific query histories tied to a single user.
  • Acceptable: endpoint shapes, undocumented field names, API gotchas, observed schema drift, workarounds for CLI surfaces, generalizable pagination or retry tactics.

If a correction is only meaningful with user-specific context, it belongs in a personal note, not in the playbook amend.

Measuring the loop

beehiiv-pp-cli learnings stats reports recall hit rate, teach-to-reuse, playbook resolution rate, and candidate confirm/reject counts from the local learn_events table. Rates are null until they have a denominator; everything stays on this machine. Use it to check whether the loop is earning its keep for this CLI.

Disabling learning

  • --no-learn on a single command short-circuits both recall and the teach write path. Use for deterministic agent flows or tests that must not be affected by accumulated learnings.
  • BEEHIIV_NO_LEARN=true in the environment globally disables the pipeline.

Agent Feedback

When you (or the agent) notice something off about this CLI, record it:

beehiiv-pp-cli feedback "the --since flag is inclusive but docs say exclusive"
beehiiv-pp-cli feedback --stdin < notes.txt
beehiiv-pp-cli feedback list --json --limit 10

Entries are stored locally as feedback.jsonl under the resolved data dir. They are never POSTed unless BEEHIIV_FEEDBACK_ENDPOINT is set AND either --send is passed or BEEHIIV_FEEDBACK_AUTO_SEND=true. Default behavior is local-only.

Write what surprised you, not a bug report. Short, specific, one line: that is the part that compounds.

Output Delivery

Every command accepts --deliver <sink>. The output goes to the named sink in addition to (or instead of) stdout, so agents can route command results without hand-piping. Three sinks are supported:

SinkEffect
stdoutDefault; write to stdout only
file:<path>Atomically write output to <path> (tmp + rename)
webhook:<url>POST the output body to the URL (application/json or application/x-ndjson when --compact)

Unknown schemes are refused with a structured error naming the supported set. Webhook failures return non-zero and log the URL + HTTP status on stderr.

Named Profiles

A profile is a saved set of flag values, reused across invocations. Use it when a scheduled or recurring agent reuses the same saved flags while providing different input each run.

beehiiv-pp-cli profile save briefing --json
beehiiv-pp-cli --profile briefing advertisement-opportunities mock-value
beehiiv-pp-cli profile list --json
beehiiv-pp-cli profile show briefing
beehiiv-pp-cli profile delete briefing --yes

Explicit flags always win over profile values; profile values win over defaults. agent-context lists all available profiles under available_profiles so introspecting agents discover them at runtime.

Exit Codes

CodeMeaning
0Success
2Usage error (wrong arguments)
3Resource not found
4Authentication required
5API error (upstream issue)
7Rate limited (wait and retry)
10Config error

Argument Parsing

Parse $ARGUMENTS:

  1. Empty, help, or --help → show beehiiv-pp-cli --help output
  2. Starts with install → ends with mcp → MCP installation; otherwise → see Prerequisites above
  3. Anything else → Direct Use (execute as CLI command with --agent)

MCP Server Installation

Install the MCP binary from this CLI's published public-library entry or pre-built release, then register it:

bash
claude mcp add beehiiv-pp-mcp -- beehiiv-pp-mcp

Verify: claude mcp list

Direct Use

  1. Check if installed: which beehiiv-pp-cli If not found, offer to install (see Prerequisites at the top of this skill).
  2. Match the user query to the best command from the Unique Capabilities and Command Reference above.
  3. Execute with the --agent flag:
    bash
    beehiiv-pp-cli <command> [subcommand] [args] --agent
  4. If ambiguous, drill into subcommand help: beehiiv-pp-cli <command> --help.

Frequently asked questions

What does the Pp Beehiiv AI skill do?

Sync your Beehiiv audience to a local database and answer growth questions offline in one command. Trigger phrases: `check my beehiiv growth`, `subscriber sources`, `which send time works best`, `compare my publications`, `lookup subscriber email`, `use beehiiv`, `run beehiiv`.

Why use Pp Beehiiv on TypingMind?

Because you install it once and use it with any model. Pp Beehiiv is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pp Beehiiv in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mvanhorn/printing-press-library/tree/main/cli-skills/pp-beehiiv. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pp Beehiiv?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pp Beehiiv?

As many as you like. As long as a model supports skills, you can use Pp Beehiiv with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pp Beehiiv AI skill free?

Yes. It is published on GitHub by mvanhorn under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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