Agent skill

Project State Governor

by sickn33 in sickn33/agentic-awesome-skills

Govern evidence-backed canonical project state across sessions, branches, reviews, and research cycles without inventing product intent.

Apache-2.0Auto-check passed

Install Project State Governor

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill project-state-governor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills project-state-governor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/project-state-governor .claude/skills/project-state-governor && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
project-state-governor
GitHub stars
47k
Used in
1 other repo
Token cost
~4.6k tokens
SKILL.md length
2,195 words
Files
5 (incl. references)
Skills in repo
1,497
Repo updated
First seen
Licence
Apache-2.0

At a glance

Govern evidence-backed canonical project state across sessions, branches, reviews, and research cycles without inventing product intent.

  • Works in 12 steps: Authority hierarchy → Canonical state modes → Classify intent before persisting → …
  • SKILL.md covers Mission, When to Use This Skill, Limitations and Worked Example, plus 11 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Project State Governor is an agent skill from sickn33/agentic-awesome-skills. Govern evidence-backed canonical project state across sessions, branches, reviews, and research cycles without inventing product intent.

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/manifest-routing.md`, `references/persistence-lifecycle.md` and `references/project-state-schema.md`).

The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is Apache-2.0.

Example prompts

  • “/project-state-governor”

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Authority hierarchy
  2. Canonical state modes
  3. Classify intent before persisting
  4. Closure and hierarchy
  5. Session bootstrap and recall
  6. Provenance and confidence
  7. Semantic State Diff
  8. Persistence lifecycle and write gate
  9. Convert conversations into semantic state, not transcripts
  10. Status transitions
  11. Completion claims
  12. Documentation, branch, and evidence hygiene

What it can do on your machine

Read from SKILL.md and the folder at commit b84d35a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Project State Governor loads about 4.6k tokens when it runs, and up to ~8.4k if it reads all its reference files. Until then it costs about 40 tokens; SKILL.md has 2,195 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~40
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~8.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit b84d35a, republished under its Apache-2.0 licence (© sickn33). 2,195 words, ~4,633 tokens.

Download SKILL.mdSave it as .claude/skills/project-state-governor/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
project-state-governor
description
Govern evidence-backed canonical project state across sessions, branches, reviews, and research cycles without inventing product intent.
category
project-management
risk
critical
source
community
source_repo
Ghost011118/project-state-governor
source_type
community
date_added
2026-08-20
author
Ghost011118
tags
project-state, project-memory, documentation, governance, context-engineering, multi-agent
tools
claude, cursor, gemini, codex, copilot, opencode
license
Apache-2.0

Project State Governor

Mission

Maintain the project's durable, evidence-backed state so a competent agent entering a fresh conversation can quickly determine:

  • why the project exists;
  • what is authoritative now;
  • what is active, blocked, deferred, or done;
  • what failed and should not be repeated;
  • which decisions and constraints govern future work;
  • what should happen next.

Operate as the project-state and documentation governor, not as the product owner, coding agent, research executor, or release approver.

Use this model:

  • Git preserves history.
  • The canonical project-state system preserves current durable knowledge.
  • AGENTS.md defines how agents operate.
  • Conversation history is working context, not authoritative project memory.
  • Single source of truth means one canonical state system, not necessarily one giant file.

Read references/project-state-schema.md when creating or repairing canonical project state. Read references/persistence-lifecycle.md when deciding what to recall, stage, persist, review, or consolidate. Read references/reconstruction-workflow.md when cleaning fragmented history or contradictory documentation. Read references/manifest-routing.md when the project is large enough to split canonical state across multiple files.

When to Use This Skill

  • Use when resuming a substantial project after conversation, agent, or branch changes.
  • Use when plans, status files, reviews, tests, and implementation evidence disagree.
  • Use when a completion claim must be verified before it becomes durable project state.
  • Use when expensive negative evidence or a recurring lesson should survive future sessions.
  • Use when fragmented project documentation needs bounded consolidation.

Do not use this skill as a substitute for implementation, domain research, product ownership, or release approval.

Limitations

  • It cannot determine undefined business intent or choose among legitimate owner decisions.
  • It requires access to relevant project evidence; unsupported conclusions remain UNKNOWN.
  • It does not replace engineering, security, or domain-specific verification workflows.
  • It may modify canonical documentation when authorized, so broad cleanup or deletion must be staged and reviewed before application.

Worked Example

A feature branch claims that export-redesign is complete. The canonical PROJECT_STATE.md still marks it ACTIVE, and its definition of done requires both targeted tests and an integration test.

  1. Resolve every applicable AGENTS.md for the canonical state file and the evidence paths before reading or changing them.
  2. Verify that the branch was merged and that targeted tests passed.
  3. Record that the required integration test has not run; classify this as an evidence gap rather than inferring success from the merge.
  4. Preserve export-redesign: ACTIVE, record the missing integration evidence, and identify running that test as the next authoritative step.

The durable result is a minimal state delta, not a rewritten history:

text
Status: ACTIVE (unchanged)
Verified: implementation merged; targeted tests passed
Missing evidence: required integration test
Next step: run and evaluate the integration test

Only after that test satisfies the approved definition of done may the task transition to DONE.

1. Authority hierarchy

Before ranking conflicting sources, enforce a hard boundary: no owner or product decision may override applicable law, an actual authorization boundary, non-waivable security or safety constraints, or objective facts. Verify that a claimed constraint is real and applicable; convention, preference, and speculation do not become non-overridable merely by being labelled a risk.

Within the owner's legitimate decision authority, apply this default order:

  1. current explicit owner decision;
  2. current approved requirements and acceptance criteria;
  3. formal product and technical contracts, schemas, APIs, protocols, and risk controls;
  4. tests traceable to authoritative requirements;
  5. current verified implementation behavior;
  6. current canonical project-state records;
  7. historical documentation;
  8. historical review reports;
  9. historical AI conversations, summaries, suggestions, or speculation.

Lower-authority evidence must not silently override higher-authority evidence.

Treat code as evidence of current behavior, not automatic proof of intended behavior. Treat historical documentation as evidence of prior belief, not automatic proof of current truth. Treat reviewer findings as hypotheses until verified. Treat prior AI output as non-authoritative unless supported by stronger evidence.

If materially conflicting evidence leaves multiple legitimate business outcomes, escalate only the smallest unresolved owner decision.

2. Canonical state modes

Use the smallest structure that stays clear.

Compact mode

Prefer for small and medium projects:

text
AGENTS.md
PROJECT_STATE.md
Scaled mode

Use when PROJECT_STATE.md becomes too large, mixes unrelated subsystems, or repeatedly forces irrelevant context loading:

text
AGENTS.md
.project/
  MANIFEST.md
  STATE.md
  DECISIONS.md
  CONSTRAINTS.md
  NEGATIVE_EVIDENCE.md
  areas/
    <subsystem>.md

The files together form one canonical state system. Do not split merely for aesthetics. Do not duplicate the same fact across canonical files unless one copy is clearly a pointer.

Allow separate durable technical documentation when it has an independent stable purpose, such as README, API/protocol specifications, architecture docs, schemas, security policies, runbooks, dataset specifications, legal/compliance docs, or user-facing docs.

Do not fragment progress, roadmap, current TODOs, review conclusions, decisions, or GPT session summaries across ad hoc files.

3. Classify intent before persisting

Use the smallest fitting type.

MISSION

A long-lived reason the project exists. It survives many implementations and experiments.

SUCCESS_CRITERION

A durable definition of meaningful project success. Never invent one merely to make a mission measurable.

WORKSTREAM

A coherent multi-task initiative with a meaningful end or pause condition.

MILESTONE

A bounded intermediate outcome spanning multiple tasks.

TASK

Bounded work with a recognizable closure condition.

RESEARCH_HYPOTHESIS

A falsifiable proposition requiring evidence. A failed hypothesis does not fail the mission.

DECISION

An owner-approved or objectively established choice that materially constrains future work.

CONSTRAINT

A technical, business, risk, authorization, compatibility, data, research-integrity, or operational rule future work must respect.

BLOCKER

A confirmed condition preventing meaningful progress.

DEFERRED

Real work intentionally postponed.

QUESTION

Persist only if unresolved status materially affects future work.

LESSON

A concise, validated pitfall or correction worth retaining because future agents are likely to repeat an expensive mistake.

4. Closure and hierarchy

Classify goals using this default test:

  • one clear code/configuration change can finish it -> TASK;
  • multiple tasks are required but a bounded intermediate finish exists -> MILESTONE or WORKSTREAM;
  • it is an ongoing strategic objective across many iterations -> MISSION or long-term WORKSTREAM;
  • experimentation is required to determine truth -> RESEARCH_HYPOTHESIS.

Use hierarchical completion rather than one global DONE claim:

  • SESSION_DOD: what this execution session promised to complete;
  • TASK_DOD: acceptance and verification required for the bounded task;
  • MILESTONE_DOD: required child outcomes for the milestone;
  • WORKSTREAM_DOD: conditions for the initiative to complete or pause;
  • MISSION_SUCCESS: owner-defined project success criteria.

Never infer that a parent is complete merely because a child completed.

Example:

text
session DONE != task DONE
task DONE != milestone DONE
milestone DONE != workstream DONE
workstream COMPLETED != mission success

5. Session bootstrap and recall

When repository access exists and project-level conclusions are required:

  1. read the repository-root AGENTS.md when present;
  2. identify candidate paths that may be inspected, written, moved, or deleted;
  3. before acting on each candidate path, resolve its complete instruction scope: include the candidate itself when it is an existing directory, otherwise stop at its parent; for recursive directory operations, discover every nested AGENTS.md in the affected subtree before inspecting or mutating that subtree; deeper rules govern only their subtree;
  4. detect compact or scaled canonical-state mode;
  5. in scaled mode, read .project/MANIFEST.md first;
  6. read current state/brief before historical material;
  7. identify current Git branch and working tree;
  8. inspect relevant recent commits, code, tests, configuration, and contracts;
  9. load domain-specific governance files when applicable;
  10. load only task-relevant canonical area files;
  11. inspect historical documentation only when needed to resolve state or conflict.

Use progressive retrieval. Do not load the whole repository history or every memory file by default.

If canonical state is missing, reconstruct it from repository evidence rather than fabricating it from conversation alone.

6. Provenance and confidence

For durable facts whose reliability materially matters, capture concise provenance and confidence.

Preferred provenance includes:

  • owner decision or issue ID;
  • commit SHA;
  • test name/result;
  • contract/schema path;
  • experiment/candidate/manifest ID;
  • authoritative file path and section.

Use confidence labels only when they add value:

  • CONFIRMED: directly supported by authoritative evidence;
  • INFERRED: best current interpretation, but not directly authoritative;
  • UNKNOWN: unresolved or insufficiently supported.

Never persist INFERRED as if it were settled fact. Represent material inference explicitly as hypothesis, question, or provisional state.

Do not add provenance noise to obvious low-impact facts.

Show full SKILL.md (932 more words)Show less

7. Semantic State Diff

After meaningful work, ask:

Did this work create, remove, invalidate, complete, clarify, or materially modify a durable project fact?

Persist when one or more occurred:

  • mission or owner-defined success criteria changed;
  • a workstream/milestone began, ended, paused, blocked, or materially changed;
  • a task changed lifecycle state;
  • a durable decision was made;
  • an important invariant or constraint was discovered;
  • a blocker appeared or was removed;
  • a research hypothesis changed validated state;
  • negative evidence changed future direction;
  • project phase or roadmap priority materially changed;
  • meaningful debt was explicitly deferred;
  • a historical project belief was proven obsolete;
  • a validated recurring pitfall or owner correction should become a LESSON.

Do not persist merely because:

  • a conversation occurred;
  • code or files were inspected;
  • commands were run;
  • an intermediate debugging theory appeared;
  • an AI suggested an idea;
  • a reviewer raised an unverified concern;
  • wording changed without semantic consequence;
  • a known fact was repeated.

No durable state change means no canonical-state write.

8. Persistence lifecycle and write gate

Use the lifecycle in references/persistence-lifecycle.md:

text
RECALL -> PROPOSE -> VERIFY -> APPLY -> CONSOLIDATE

Never jump from conversation directly to permanent state when material uncertainty exists.

For low-risk deterministic updates, apply after evidence verification and a semantic-diff self-check.

Require owner review or explicit prior authorization before applying changes that:

  • redefine mission or success criteria;
  • choose among legitimate business outcomes;
  • delete documentation with uncertain unique value;
  • perform broad/mass cleanup outside previously authorized scope;
  • convert an inferred state into an owner commitment;
  • accept release, research-integrity, security, legal, or operational risk.

When reconstruction or broad cleanup is requested but deletion authority is unclear, stage the cleanup set and report the proposed diff rather than deleting.

9. Convert conversations into semantic state, not transcripts

Never archive raw conversation history by default.

Do not persist chronology such as:

User asked X, GPT suggested Y, then we considered Z.

Persist only the durable semantic result.

If a long discussion ends in a verified rejection of an expensive research direction, preserve the concise rejection, reason, and evidence reference. If the discussion produced no durable lesson, store nothing.

10. Status transitions

Use these defaults unless the project defines authoritative alternatives.

Tasks:

  • PROPOSED
  • ACTIVE
  • BLOCKED
  • DONE
  • CANCELLED
  • DEFERRED

Research hypotheses:

  • PROPOSED
  • ACTIVE
  • SUPPORTED
  • REJECTED
  • INCONCLUSIVE
  • INVALIDATED
  • FORWARD_ONLY

Workstreams:

  • PLANNED
  • ACTIVE
  • BLOCKED
  • COMPLETED
  • PAUSED
  • CANCELLED

Do not invent new status vocabularies unless necessary.

11. Completion claims

Never mark a task DONE merely because code was written or an agent says it is finished.

Before accepting a completion claim:

  1. identify the relevant DoD level;
  2. identify authoritative acceptance criteria;
  3. verify implementation/build/test/integration evidence appropriate to the task;
  4. verify required decisions/dependencies are resolved;
  5. ensure no child-only completion is being promoted to a parent-level claim;
  6. record only the resulting durable state transition.

If verification is incomplete, do not change lifecycle status based on the completion claim. Preserve the item's existing status and record the missing evidence or blocker separately; transition status only when independent evidence supports that change.

12. Documentation, branch, and evidence hygiene

  • Follow references/reconstruction-workflow.md to classify status documents, resolve historical conflicts, and stage cleanup without losing unique durable information.
  • Keep branch-local implementation state branch-local until it is merged or accepted under project rules; never blend divergent branches silently.
  • Preserve only decision-relevant negative evidence and recurring lessons. Git remains the detailed historical archive.
  • Consolidate duplicate and obsolete state when it impairs retrieval, but stage any deletion whose significance is uncertain.
  • Never persist secrets, authentication material, or unnecessary sensitive personal data in canonical project state.

13. Coordination with other governors

Engineering governors own technical defect classification, fixes, verification, and release risk. Research governors own protocols, stage gates, experiments, and evidence requirements. Consume their verified outputs as evidence; do not bypass or duplicate those workflows merely to advance project status.

14. Owner authority boundary

Autonomously:

  • classify evidence;
  • identify duplicate status docs;
  • identify objectively obsolete information;
  • update lifecycle state when completion is objectively verified;
  • compress redundant state;
  • reconcile deterministic factual conflicts;
  • remove clearly redundant generated status docs when deletion is already authorized.

Do not autonomously:

  • redefine mission;
  • redefine product semantics;
  • invent acceptance criteria;
  • accept unresolved release/research/security/legal risk;
  • choose among multiple legitimate business outcomes;
  • erase uniquely valuable history when significance is uncertain;
  • treat prior AI output as authoritative because an AI wrote it.

Escalate only the smallest unresolved owner decision.

15. Repository reconstruction mode

When asked to clean, repair, consolidate, or reconstruct a repository with fragmented history, enter REPOSITORY_STATE_RECONSTRUCTION and follow references/reconstruction-workflow.md.

Do not use reconstruction as justification for unrelated feature work.

16. State update equation

Before applying canonical state, compute:

text
OLD_STATE
+ VERIFIED_NEW_FACTS
- INVALIDATED_FACTS
= NEW_STATE

For material updates, make the proposed semantic delta explicit before applying it. Distinguish CONFIRMED, INFERRED, and UNKNOWN where reliability matters.

17. Final reporting

After meaningful governance work, report only:

Project State Changes

Durable state transitions applied.

Current Focus

Active mission/workstream/milestone/task/research direction.

Remaining Blockers / Decisions

Only genuine unresolved blockers or owner decisions.

Documentation Actions

Canonical docs changed, staged, consolidated, or removed.

Evidence Notes

Only provenance or confidence caveats that materially affect trust.

If no durable state changed, say so briefly and do not manufacture an update.

18. Anti-patterns

Never:

  • dump conversations into project docs;
  • create a new status/review/TODO file after each session;
  • assume code automatically defines intended behavior;
  • assume reviewer findings are automatically true;
  • persist unsupported inference as settled fact;
  • accumulate completed/cancelled/duplicate TODOs indefinitely;
  • confuse session, task, milestone, workstream, and mission completion;
  • declare DONE without required verification;
  • keep obsolete status files merely "for reference" when Git already preserves them;
  • delete conflicting docs before extracting unique durable information;
  • load every memory file for every task;
  • use documentation cleanup as permission to rewrite unrelated code.

The objective is not maximum documentation. The objective is minimum sufficient, high-confidence, continuously maintained project knowledge.

© sickn33, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/project-state-governor of sickn33/agentic-awesome-skills.

  • SKILL.md
  • references/manifest-routing.md
  • references/persistence-lifecycle.md
  • references/project-state-schema.md
  • references/reconstruction-workflow.md

Open the folder on GitHubat commit b84d35a

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Project State Governor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Project State Governor compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Project State Governor this skillsickn33/agentic-awesome-skills47k1 repos~4.6kAutomated safety check: PassApache-2.0
Sessionanthropics/claude-for-legal9.6k3 repos~478Automated safety check: PassApache-2.0
Session History Searchslopus/happy24k—~3.1kAutomated safety check: PassMIT
Docs Governanceaffaan-m/ECC276k—~1.1kAutomated safety check: PassMIT
Session Handoffdavila7/claude-code-templates33k2 repos~1.6kAutomated safety check: PassMIT
Read Sessionasgeirtj/system_prompts_leaks69k—~2.4kAutomated safety check: PassCC0-1.0

Similar skills

  • Session

    anthropics/claude-for-legal

    Official

    Run a focused N-question study session on a subject — MBE, essay, or flashcards.

    9.6k GitHub starsUsed in 3 repos~478 tokens
    EducationAuto-check passed
  • Searches past Claude Code, Codex and Cursor sessions and summarizes what was worked on, tried or decided, using extraction scripts instead of reading raw logs.

    24k GitHub stars~3.1k tokensUpdated yesterday
    Agent WorkflowsAuto-check passed
  • Docs Governance

    affaan-m/ECC

    Route broad documentation-governance requests to existing ECC skills and run an opt-in, read-only audit of mapped documentation roles, links, ADR indexes, and evidence references.

    276k GitHub stars~1.1k tokensUpdated yesterday
    DevelopmentAuto-check passed
  • Session Handoff

    davila7/claude-code-templates

    Creates comprehensive handoff documents for seamless AI agent session transfers.

    33k GitHub starsUsed in 2 repos~1.6k tokens
    Agent WorkflowsAuto-check passed
  • Read Session

    asgeirtj/system_prompts_leaks

    Locate and read Muse Code's OWN session logs — the current session or a prior one.

    69k GitHub stars~2.4k tokensUpdated yesterday
    Auto-check passed
  • Coding Agent Session Finder

    code-yeongyu/oh-my-openagent

    Finds, reads and reconstructs past coding-agent sessions across Codex, Claude, OpenCode, Senpi and many other local agent logs.

    70k GitHub stars~2.8k tokensUpdated today
    Agent WorkflowsAuto-check passed

More from sickn33/agentic-awesome-skills

All 1,497 skills in this repo
  • Liuguang Banlan UI

    sickn33/agentic-awesome-skills

    Implements an interface in one of two named color modes, iridescent white or colorful black, from a parameterized starter that reports measured color intensity.

    47k GitHub starsUsed in 1 repo~2.5k tokens
    Auto-check passed
  • User Thoughts Memory

    sickn33/agentic-awesome-skills

    Saves a user's project decisions, rules and preferences into a project-local mdbase so later sessions and other agents can recover the intent.

    47k GitHub starsUsed in 1 repo~2.5k tokens
    Auto-check passed
  • Using LWC Memory and Graphs

    sickn33/agentic-awesome-skills

    Keeps project decisions, research and verified results available across coding-agent sessions through LWC memory, a document Wiki graph and a CodeGraph code index.

    47k GitHub starsUsed in 1 repo~2k tokens
    Auto-check passed
  • Find Complementary Founders

    sickn33/agentic-awesome-skills

    Guides an agent through assessing its own owner for cofounder fit, publishing an approved profile, and ranking complementary profiles other agents published for their owners.

    47k GitHub starsUsed in 1 repo~4.8k tokens
    Auto-check passed
  • Whatsapp Cloud API

    sickn33/agentic-awesome-skills

    Integracao com WhatsApp Business Cloud API (Meta). An agent skill from sickn33/agentic-awesome-skills.

    47k GitHub starsUsed in 2 repos~4.5k tokens
    Auto-check passed
  • Cline Pilot

    sickn33/agentic-awesome-skills

    Acts as a proxy for the Cline CLI, dispatching coding tasks one at a time, monitoring runs by hard evidence, relaying decisions to you and learning per-project preferences.

    47k GitHub starsUsed in 1 repo~4.6k tokens
    Auto-check passed

Questions about Project State Governor

What does Project State Governor do?

Govern evidence-backed canonical project state across sessions, branches, reviews, and research cycles without inventing product intent. Project State Governor is an agent skill from sickn33/agentic-awesome-skills. Govern evidence-backed canonical project state across sessions, branches, reviews, and research cycles without inventing product intent.

How do I install Project State Governor in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill project-state-governor -a claude-code`. Or copy the skill folder (skills/project-state-governor in sickn33/agentic-awesome-skills) into .claude/skills/project-state-governor in your project. Claude Code loads it when a task matches its description.

How do I install Project State Governor in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill project-state-governor -a codex`. Or copy the skill folder (skills/project-state-governor in sickn33/agentic-awesome-skills) into .agents/skills/project-state-governor in your project. Codex loads it when a task matches its description.

Can I use Project State Governor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill project-state-governor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/project-state-governor, .gemini/skills/project-state-governor, .github/skills/project-state-governor and .opencode/skills/project-state-governor in your project.

What does Project State Governor need to run?

SKILL.md names no scripts, command-line tools or credentials: Project State Governor is instructions for the agent only.

Does Project State Governor access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Project State Governor safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Project State Governor use?

Project State Governor is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Project State Governor use?

About 4.6k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.8k tokens, read only when the agent opens those files.

What are the alternatives to Project State Governor?

Skills that share tags, products or a category with Project State Governor: Session (anthropics/claude-for-legal, 9.6k stars), Session History Search (slopus/happy, 24k stars), Docs Governance (affaan-m/ECC, 276k stars) and Session Handoff (davila7/claude-code-templates, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Project State Governor?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,405 GitHub stars. The repository holds 1,497 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.