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Deprecation

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ericrisco
deprecation

Use when retiring a public API, feature, integration, service or legacy path without abandoning consumers. Inventories usage, classifies advisory vs compulsory migration, ships compatibility/tooling, assigns owners and gates removal on evidence. NOT live schema expand-contract (`db-migrations`), NOT replacement API design (`api-design`).

Overview

Publisherericrisco
Repositoryrsc-harness
Skill namedeprecation
Stars
239
Forks
24
Bundled files
1
LicenseMIT
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Deprecation 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.
    https://github.com/ericrisco/rsc-harness/tree/main/skills/deprecation
  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/ericrisco/rsc-harness.git /tmp/rsc-harness
mkdir -p .claude/skills
cp -r /tmp/rsc-harness/skills/deprecation .claude/skills/deprecation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deprecation 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 Deprecation 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 Deprecation 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.

deprecation — removal is a consumer migration

Deprecation is not a date in a changelog. It is the controlled transfer of real consumers from an old contract to a supported replacement, followed by evidence that removal no longer breaks anyone important.

This skill owns the cross-consumer program. It delegates the replacement interface to ../api-design/SKILL.md, live schema mechanics to ../db-migrations/SKILL.md, release/version mechanics to ../git-workflow/SKILL.md, and rollout/rollback execution to ../deployment/SKILL.md.

The retirement sequence

text
INVENTORY → CLASSIFY → ENABLE → NOTIFY → MIGRATE → OBSERVE → REMOVE

1. INVENTORY the contract and consumers

Identify:

  • exact endpoints, events, schemas, flags, SDK methods, jobs, services and docs being retired;
  • internal and external consumers, owners and contractual notice periods;
  • traffic/usage by consumer, version and operation;
  • data written only by the old path and compatibility obligations;
  • support, reseller or offline consumers invisible to runtime telemetry;
  • current fallback and restoration options.

“No known users” is not an inventory. Query telemetry, code search, dependency graphs, access keys, support records and account owners. Record where visibility is incomplete.

2. CLASSIFY the migration

  • Advisory: the old path remains supported; migration is encouraged for benefit or future-proofing.
  • Compulsory: support will end or continued use creates unacceptable security, reliability, legal or operating risk.

Only compulsory migrations justify a removal deadline. State the forcing reason and who has authority to accept exceptions. A deadline should respect contracts, effort and evidence; do not import a universal 30/60/90-day calendar.

3. ENABLE migration before announcing removal

The replacement must be usable first:

  • compatible contract or adapter where feasible;
  • migration guide with old → new mappings and changed semantics;
  • tooling, codemod, SDK or dual-write/read path for repetitive work;
  • test/sandbox path and representative examples;
  • rollback or temporary compatibility mode;
  • ownership for data backfill and reconciliation.

For database changes, use expand → backfill → switch reads/writes → contract through ../db-migrations/SKILL.md. Do not promise a generic down migration for irreversible data transformations; prove the actual restoration/reconciliation path instead.

4. NOTIFY through machine and human channels

Use the channels the consumer will actually see: response headers, compiler/runtime warnings, API dashboards, release notes, direct account contact, support and status communications. A warning must name the replacement, action, consequence, evidence link and earliest removal condition.

Versioned public APIs should follow their compatibility policy and SemVer where it applies. Machine warnings without a migration guide create noise; an email without runtime identification misses the real owner. Use both when the surface permits.

5. MIGRATE with explicit ownership

The team introducing the deprecation owns the common migration path: inventory, docs, automation, default internal consumers and escalation. Consumer teams own domain-specific acceptance and scheduling, not rediscovering the replacement.

Track each consumer as: uncontacted, acknowledged, testing, migrated, exempted with expiry, unreachable, or blocked. Give blockers an owner and next action. Reseller-managed or unknown consumers need a separate reachability plan; do not silently exclude them from the denominator.

6. OBSERVE real cutover

Instrument old-path usage by consumer and operation, plus errors on the replacement. Where risk warrants it, shadow or dual-run and compare results before switching authority. Dashboards must distinguish legitimate residual traffic, retries and synthetic probes from active dependency.

Define the removal gate up front, for example:

  • no non-exempt production use for a representative window;
  • every contractually covered consumer notified and migrated or explicitly exempted;
  • replacement error/SLO health acceptable;
  • rollback/compatibility response tested;
  • support, docs and on-call ready for late discoveries.

The representative window depends on consumer cadence. A monthly batch needs more than a quiet week.

7. REMOVE in a reversible order

Disable entry first, observe, then delete implementation, flags, compatibility code, credentials, dashboards and documentation that exist only for the old path. Preserve audit/history records. Update dependency and ownership maps so the retired system does not remain a zombie operational obligation.

If unexpected material traffic appears, re-enable the bounded compatibility path and return to migration. Do not restore an undocumented permanent fork.

Deprecation record

markdown
# Deprecation — <old> → <replacement>

## Classification and reason
Advisory/compulsory · forcing reason · authority · notice constraints.

## Inventory
Contracts · consumers · owners · baseline usage · visibility gaps.

## Migration path
Compatibility · guide/tooling · data plan · rollback/reconciliation.

## Consumer ledger
Consumer · state · owner · last old-path use · blocker/exception expiry.

## Removal gate and evidence
Window · zero-use evidence · replacement health · support/rollback readiness.

## Removal log
Disabled · observed · deleted · residual artifacts.

Anti-patterns

SmellCorrection
The calendar arrives while material traffic remainsHold removal; the gate is evidence, not date alone.
Every consumer writes the same adapterThe deprecating team owns common tooling and default migrations.
Internal code search proves external zero-useCombine runtime identity, contracts, support and account ownership.
Temporary compatibility has no owner or expiryTrack an explicit exception with accountable owner and end condition.
Deprecation silently grants deploy authorityKeep live rollout/rollback explicit through deployment.

Orientación (siempre)

Habla con la voz de orient: frases cortas, una idea por frase, y cada respuesta se entiende sola. Registro técnico o con analogías según technical_level en 02-DOCS/wiki/harness/user-profile.md. Cierra cada turno con el bloque-brújula (📍 dónde estás · ➡️ siguiente, terminando en pregunta; ✅ y 🧭 cuando hay algo hecho o decidido). Nunca termines en seco. Protocolo completo: skill orient → skills/orient/references/orientation-contract.md. (Defiere a suggest el "¿instalo la skill que falta?".)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Deprecation AI skill do?

Use when retiring a public API, feature, integration, service or legacy path without abandoning consumers. Inventories usage, classifies advisory vs compulsory migration, ships compatibility/tooling, assigns owners and gates removal on evidence. NOT live schema expand-contract (`db-migrations`), NOT replacement API design (`api-design`).

Why use Deprecation on TypingMind?

Because you install it once and use it with any model. Deprecation 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 Deprecation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ericrisco/rsc-harness/tree/main/skills/deprecation. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Deprecation?

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 Deprecation?

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

Is the Deprecation AI skill free?

Yes. It is published on GitHub by ericrisco under the MIT 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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