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Subagent Governance

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Firstp1ck
subagent-governance

Delegation admissibility governance for a parent orchestrator. Use when deciding whether to launch, sequence, replace, or accept one or more delegated child runs while preserving role fit, plan-backed worker contracts, one-writer isolation, bounded retry safety, and reviewer finding disposition. Covers admissibility only; a harness keeps its own runtime mechanics documentation.

Overview

PublisherFirstp1ck
Repositorypi-coding-agent-forge
Skill namesubagent-governance
Stars
93
Forks
22
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

    Published by Firstp1ck on GitHub. Read the source before you install it.

Installation

Install the Subagent Governance 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/Firstp1ck/pi-coding-agent-forge/tree/main/pi-skill-subagent-governance/skills/subagent-governance
  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/Firstp1ck/pi-coding-agent-forge.git /tmp/pi-coding-agent-forge
mkdir -p .claude/skills
cp -r /tmp/pi-coding-agent-forge/pi-skill-subagent-governance/skills/subagent-governance .claude/skills/subagent-governance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Subagent Governance 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 Subagent Governance 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 Subagent Governance 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.

Subagent Governance

Use this skill in the parent orchestrator session before delegating work to child agents, before replacing a child that did not deliver, and when accepting delegated results. It decides which delegation shapes are allowed and which evidence is required. It is guidance, not a runtime guard: loading it does not install a package, enable an integration, change settings, or block a tool call.

Scope and Boundary

  • This skill controls admissibility. Whether delegation is allowed at all, how many children of which kinds may be declared, who may write, what a worker must be told, what a handoff must return, when a replacement launch is legal, and how a reviewer finding is dispositioned.
  • The harness's delegation documentation controls runtime mechanics. Tool schemas, action names, launch/monitor/wait syntax, context modes, agent and chain authoring, configuration, and error handling. In Pi, the installed pi-subagents skill remains canonical for those mechanics; this skill does not restate, replace, or override it, and it is not a second mechanics reference.
  • Parent-only. Do not inject or follow this skill inside a spawned child. A child does not own delegation, fanout, integration, or completion decisions. The one exception is a child that the parent explicitly assigned bounded fanout; it stays inside that assignment.
  • Admissibility and runtime success are independent. An admissible shape can still fail at runtime, and no runtime capability, convenience command, or saved workflow makes a noncompliant shape admissible.

When to Use

Use when the parent is deciding whether to delegate, what to declare in a delegation request, how to keep concurrent work safe, how to react to a failed or partial delegated run, or what to do with reviewer output.

Do not use for:

  • Launch syntax, tool arguments, action names, context modes, scheduling, or error messages — those belong to the harness's mechanics documentation.
  • Creating, editing, disabling, or ejecting agents and saved workflows.
  • Cost, usage, or status inspection with no pending delegation decision.
  • Work the parent should simply do itself, such as a direct edit, a direct answer, or a single-file fix.
  • Feature scope, plan structure, completion gates, or report obligations, which belong to the feature workflow policy in use.

Should trigger

  • "Split this migration across several agents before anyone starts writing."
  • "One delegated run failed mid-call — decide what to relaunch without touching the runs still going."
  • "Two implementation runs finished; decide how to integrate them and what review they need."
  • "Reviewers disagree about this integrated change; decide what to accept before a fix pass."

Should not trigger

  • "What arguments does the delegation tool take for a scheduled run?"
  • "Create a new custom agent file with a different model and thinking level."
  • "Show the token cost of the last background runs."
  • "Fix the null check in the auth module."
  • "Write the final HTML report for the finished feature."

Ambiguous requests

"Delegate this to an agent" mixes an admissibility question with a mechanics question. Resolve admissibility here first — including whether delegating at all is allowed — then use the harness's mechanics documentation to express the approved shape.

Invocation Design

  • Invocation mode: model-invoked after explicit package enablement.
  • Leading concept: delegation admissibility governance.
  • Deliberately named subagent-governance so it does not collide with, shadow, or substitute for a harness mechanics skill such as pi-subagents.
  • Creation of this package is inert. Review it before any later installation or enablement, which requires explicit authorization.

Reference Router

Read the matching reference before acting. Paths are relative to this SKILL.md.

SituationRead
Writing a worker task, checking a returned handoff, supervising integration, or dispositioning reviewer findingsreferences/WORKER-AND-REVIEW-CONTRACTS.md
A child failed, was interrupted, returned nothing, was rejected, or a whole call reported failure and replacement launches are being consideredreferences/RETRY-AND-RECOVERY.md
Mapping this governance to Pi, including discovery, launch posture, local model defaults, retry helpers, and escalationreferences/PI-EXECUTION-ADAPTER.md

The core admissibility invariants below stay in this file. References carry branch detail only; they never lower an invariant.

Inputs and Assumptions

Establish before delegating:

  • The necessary outcomes of the request, stated as outcomes rather than as agents.
  • The executable, non-disabled roles the harness actually offers, from live discovery rather than memory.
  • Repository state: clean or dirty, isolated working trees available or not, and which files each outcome must write.
  • The approved plan, decisions, and non-goals, plus the named integration owner when one exists.
  • Whether the parent is authorized to write, and whether external side effects are approved.

Assume nothing about a role's availability, a provider's health, or a child's success. Assume every child result is unverified until inspected.

Portable Workflow

  1. Confirm parent-only scope and live capability

    • Confirm this session is the parent orchestrator, that the delegation capability is active, and that the roles under consideration are executable and not disabled.
    • If the capability is unavailable, do the work directly or report the exact unavailable capability and the gate it blocks. Do not simulate delegation through shells, detached processes, or hand-managed session files.
    • Completion criterion: the parent scope, the live capability, and the executable role set are confirmed.
  2. Run the role-fit preflight and keep specialist routing balanced

    • Apply this on ordinary turns whenever delegation is plausible. Convenience commands and saved workflows are shortcuts, not prerequisites.
    • Before choosing any execution shape — including direct parent work and default worker/reviewer pairs — identify each necessary outcome, map it to a discovered executable specialist, and select every role with a distinct, material contribution.
    • Balance means equal consideration and opportunity-appropriate selection. It is not a quota, an equal invocation count, or a correction for historical usage.
    • Consider these role kinds when they materially affect the request: local reconnaissance of code, configuration, conventions, or repository state; a bounded requirements/interface/validation/handoff context artifact; implementation design, sequencing, migration, or dependency planning; current external evidence or authoritative documentation; an advisory challenge to inherited direction, architecture, or drift; a bounded generic independent outcome that fits no more specific specialist; approved implementation within assigned ownership; and independent critique of an inspectable target.
    • Advisory challenge is one capability. Never launch two advisory aliases together merely to raise a child count.
    • Resolve material uncertainty about local context, external evidence, architecture, or planning before writes. Use reviewers only after an inspectable target exists.
    • Completion criterion: every selected role has a distinct necessary outcome, and every rejected role was rejected for lack of contribution rather than for convenience.
  3. Choose the smallest justified delegation shape

    • Use zero, one, or multiple children according to the necessary outcomes. A single child is admissible when one bounded specialist outcome is useful.
    • Prefer direct parent work when delegation adds no material value, not merely because only one child would be launched.
    • Multiple children must each have a distinct, necessary outcome. Do not add duplicate, token, filler, or unrelated children to manufacture fanout.
    • Sequential child launches are allowed when dependencies, shared working-tree ownership, or integration order require them. Do not force unrelated work into one request merely to increase the declared count.
    • Workflow scripts, dynamic fanout, schedules, and direct launches have no governance-level cardinality minimum; their actual syntax and runtime behavior remain harness mechanics.
    • Completion criterion: every delegated child has a justified outcome, and the selected shape is no larger or more concurrent than the work requires.
  4. Plan and sequence implementation workers

    • Launch an implementation worker only after the parent has established an approved plan or bounded workstream contract with prerequisites, ownership, deliverables, validation, and stop conditions.
    • One implementation worker is admissible for one bounded write outcome. Several workers are admissible only when their outcomes and ownership boundaries are distinct.
    • Sequential workers may share one working tree when each predecessor has settled and the parent has inspected its state before the next launch. Concurrent writers require isolated working trees and non-overlapping ownership.
    • Dynamic worker fanout is admissible only when its expansion source, ownership rule, concurrency bound, and integration path are explicit before expansion.
    • Replacements, fallbacks, and resumes preserve the original workstream identity and do not create permission to broaden scope.
    • Completion criterion: every worker is plan-backed, dependency-ready, safely sequenced or isolated, and necessary for its assigned write outcome.
  5. Preserve one-writer isolation

    • Enforce one active writer per working tree. Never run concurrent writers in a shared tree; sequence them instead.
    • Parallel writers require clean, isolated working trees plus dependency-independent, non-overlapping ownership. Writers sharing a tree run sequentially.
    • A dirty repository must not use automatic isolated-tree fanout. Clean it only with user approval, or run sequentially in the shared tree.
    • The integration owner keeps control of shared-plan updates, decisions, integration, and completion claims. Workers must not edit the canonical plan, merge one another's branches, or spawn their own children unless explicitly assigned bounded fanout.
    • Completion criterion: every declared writer has an isolated or sequenced write path and a non-overlapping ownership boundary.
  6. Give every worker a complete task contract and require a complete handoff

    • Every worker task must state its identity and prerequisites; approved context and non-goals; the exact write boundary and forbidden or shared paths; concrete deliverables; validation; a unique output path; and stop/escalation rules for unapproved product, scope, architecture, interface, security, migration, dependency, or ownership decisions.
    • Every worker handoff must report its workstream and run identity and status; base and resulting revision when applicable; changed files and a summary; validation results and omissions; deviations, assumptions, unresolved decisions, and residual risks; and integration notes with its unique artifact path.
    • Read references/WORKER-AND-REVIEW-CONTRACTS.md before writing the task or judging the handoff.
    • Completion criterion: each worker task carries all seven contract elements and each accepted handoff carries all six report elements.
  7. Supervise integration centrally

    • Launch only dependency-ready work whose prerequisites are verified complete.
    • Count work complete only after the integration owner inspects the actual changes, the write boundary, the validation evidence, and the unresolved items. A completion claim is not evidence.
    • Treat edits outside the assigned write set, silent interface changes, missing required tests, or invented decisions as integration blockers. Revert, reassign, or request a corrected bounded change instead of normalizing scope drift.
    • Integrate isolated results in recorded order, run affected checks after each wave, and run the cross-workstream checks before review. Reviewers assess the integrated result, not isolated branches.
    • Completion criterion: every integrated result was inspected directly and every blocker was resolved or explicitly recorded.
  8. Replace failed children with bounded, deduplicated retries

    • Count successful qualifying outputs, not requested tasks, launch attempts, or occupied slots.
    • Treat a call-level failure as potentially partial. Before any replacement launch, classify every requested logical child identity. Never include a queued, running, paused, detached, or otherwise live child identity in a replacement payload, even when the original call reported failure.
    • If filtering leaves one failed or unstarted child identity, recover or relaunch only that identity when retry safety permits. Never duplicate a live child or bundle unrelated work into the replacement.
    • Never automatically replace a stopped or interrupted child, and never automatically replace a writer without inspecting its actual state and obtaining parent approval.
    • Read references/RETRY-AND-RECOVERY.md for failure classification, attempt budgets, and quorum exhaustion.
    • Completion criterion: every replacement targets only failed or unstarted slots, stays inside the attempt budget, and preserves each attempt's identity and failure class.
  9. Disposition every reviewer finding

    • Reviewer output is advisory. The integration owner independently checks every finding against the repository, the approved plan, the acceptance criteria, test results, and authoritative documentation.
    • Record exactly one disposition per finding: accepted, rejected, deferred, or needs verification, with concise evidence and rationale. Reviewer confidence, severity labels, and agreement are signals, not proof.
    • Give a fix pass only explicitly accepted findings and their verification checks. Never let a fix worker decide disposition, and never apply reviewer feedback automatically.
    • Read references/WORKER-AND-REVIEW-CONTRACTS.md for the request contract, acceptance and rejection criteria, and disagreement handling.
    • Completion criterion: every finding carries one verified disposition, and every accepted fix was revalidated.

Safety and Side Effects

This skill is read-and-decide guidance. It performs no launch, no write, and no configuration change by itself. Delegated children can write, so treat every governance decision as a safety decision.

Avoid:

  1. Spawning children through shells, nested command-line agent invocations, detached processes, or hand-managed session files.
  2. Using long blocking shell timeouts as a substitute for the harness's own lifecycle tracking.
  3. Running concurrent writers against the same working tree.
  4. Treating a worker's completion claim as reviewed, or as a substitute for required independent review.
  5. Applying reviewer feedback automatically, or letting a fix worker decide review disposition.
  6. Abandoning active background runs by ending a non-interactive turn before required results arrive.
  7. Presenting this guidance as hard enforcement. Any runtime guard the harness provides remains separate and authoritative.

Scripts, References, and Dependencies

  • references/WORKER-AND-REVIEW-CONTRACTS.md — worker task and handoff contracts, integration supervision, reviewer request contract, and finding disposition rules.
  • references/RETRY-AND-RECOVERY.md — failure classification, live-child deduplication, attempt budgets, write-safety rules, and quorum exhaustion.
  • references/PI-EXECUTION-ADAPTER.md — Pi mapping, including discovery, launch posture, local model defaults, retry helpers, escalation, and package lifecycle.
  • tests/test_skill_contract.py — contract test using the Python 3.10+ standard library only.
  • ../../tests/routing/subagent-governance.json — repository routing examples relative to this skill directory.

No runtime package dependency is required. This package implements no delegation tool, no fanout guard, no provider registry, and no runtime enforcement.

Verification

From the package root, run:

bash
npm test
npm pack --dry-run --json

A governance decision is verified when the selected roles and outcomes, worker sequencing or isolation, worker contracts, retry provenance, and finding dispositions are all inspectable in the record rather than asserted from memory.

Pi Adapter

  • In Pi, the installed pi-subagents skill stays canonical for delegation mechanics: tool schemas, actions, discovery, execution modes, context modes, authoring, configuration, and error handling. This skill adds admissibility governance on top of it and never restates its API.
  • Read references/PI-EXECUTION-ADAPTER.md for the Pi mapping of discovery, launch posture, isolation, retry helpers, escalation, and the local model defaults. Those exact model choices are Pi-local defaults only; they are not part of the portable policy.
  • When Pi feature policy is active, it owns feature outcomes, review quorum size, report obligations, and completion gates. This skill owns whether the delegation shape used to reach them is admissible.
  • Do not install this package or modify Pi settings without explicit user confirmation. A later approved local installation may use pi install <absolute-path-to-package>.

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 Subagent Governance AI skill do?

Delegation admissibility governance for a parent orchestrator. Use when deciding whether to launch, sequence, replace, or accept one or more delegated child runs while preserving role fit, plan-backed worker contracts, one-writer isolation, bounded retry safety, and reviewer finding disposition. Covers admissibility only; a harness keeps its own runtime mechanics documentation.

Why use Subagent Governance on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Firstp1ck/pi-coding-agent-forge/tree/main/pi-skill-subagent-governance/skills/subagent-governance. 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 Subagent Governance?

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 Subagent Governance?

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

Is the Subagent Governance AI skill free?

Yes. It is published on GitHub by Firstp1ck 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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