repo-context-ledger
Maintain durable, evidence-based repository context whenever an agent initializes a repository, implements or fixes behavior, refactors code, changes an interface, checkpoints or switches tasks, resumes or hands work to another AI tool, collaborates across parallel task sessions,
Supply asset profile
Research and knowledge work
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + OpenAI Agents + Cursor
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add gviiisen/repo-context-ledger --skill repo-context-ledger
Maintenance
fresh
1d since push
Risk
Risky
Permission surface may require sandboxing
GitHub quality
72
65/100 Quality · 69/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
Agent adoption scorecard
Trust, audit, and install readiness at a glance
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
RiskyA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Sandbox only
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
72 GitHub stars
Repo activity
72 stars, 0 forks
Maintenance
1d since push
License
MIT
Install
npx skills add gviiisen/repo-context-ledger --skill repo-context-ledger
Install safety
standard package or runtime install path
Permission surface
shell or command execution, filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Review before production
- The SKILL.md excerpt is truncated, but the provided content is sufficient for evaluation.
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is declared
- No Agent Proven outcome evidence yet
Agent-readable metadata
Machine-readable decision data for this skill.
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
- Research agents workflows
- Claude Code teams
- builders willing to evaluate younger projects
- Search sources
Suited agents
Install decision
- Command
- npx skills add gviiisen/repo-context-ledger --skill repo-context-ledger
- Policy
- block
- Human review
- yes
Trust and risk
- Trust
- 61/100
- Audit
- 76/100
- Risk level
- Risky
Outcome loop
- Endpoint
- /api/agent/outcome
- Event ID
- resolve
- Outcomes
- 5
Install command
npx skills add gviiisen/repo-context-ledger --skill repo-context-ledgerDo not use when
- teams that need a vendor-supported SLA
- production agents without a repository review
- The SKILL.md excerpt is truncated, but the provided content is sufficient for evaluation.
- Audit risk risky exceeds max_risk=medium
- High-risk permission hints: Shell or command execution
Alternative
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
GPT Researcher
28.0K Stars
npx skills add assafelovic/gpt-researcher
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DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent safety v2
40/100 · Avoid automatic install
This skill should not be selected by an agent without explicit human security review.
Do not auto-install. Inspect the source, dependencies, and permission surface first.
high
Shell or command execution
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Browser automation
Skill may drive a browser or interact with web pages.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
- Audit risk risky exceeds max_risk=medium
- High-risk permission hints: Shell or command execution
- Permission surface may require sandboxing
Install targets
Install this skill in your agent workflow
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install gviiisen-repo-context-ledgerAgent resolve plan
Let an agent verify fit before installing.
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20repo-context-ledger%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20repo-context-ledger%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/gviiisen-repo-context-ledger/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
Task: Use repo-context-ledger in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20repo-context-ledger%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/gviiisen-repo-context-ledger/install
Install command: npx skills add gviiisen/repo-context-ledger --skill repo-context-ledger
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/gviiisen-repo-context-ledger/install
LLM text format
/api/skills/gviiisen-repo-context-ledger/install?format=text
Find alternatives
/api/skills/search?q=repo-context-ledger&limit=3
Agent prompt
Use repo-context-ledger for this task. Review https://www.openagentskill.com/api/skills/gviiisen-repo-context-ledger/install, then install with: npx skills add gviiisen/repo-context-ledger --skill repo-context-ledgerRegistry metadata
Agent-readable profile for automatic skill selection.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/gviiisen-repo-context-ledger
LLM text
/api/registry/manifest/gviiisen-repo-context-ledger?format=text
Install alias
/api/registry/install/gviiisen-repo-context-ledger
Recommend
/api/registry/recommend?task=Use%20repo-context-ledger%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code, OpenAI Agents, Cursor
Audit report
Risky · 76/100
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
- Research agents workflows
- Claude Code teams
- builders willing to evaluate younger projects
Evidence
- recent repository activity
- install command or GitHub repo available
- 65/100 quality profile
- 8 OpenAgentSkill engagement events
review first
- The SKILL.md excerpt is truncated, but the provided content is sufficient for evaluation.
Implementation path
- 1Install it in a sandbox agent and run one Research agents task end to end.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Trust profile
Sandbox only
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
CHECK72 GitHub stars
Stars/forks activity
CHECK72 stars, 0 forks; issue activity unavailable in current metadata
Recent maintenance
PASS1d since push
License clarity
PASSMIT
Good signals
- AI review approved
- Install path is available
- Repository evidence is available
- Recently maintained repository
- Install command has no obvious high-risk pattern
- Outcome loop is ready but needs first real agent run
Review before install
- The SKILL.md excerpt is truncated, but the provided content is sufficient for evaluation.
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- GitHub adoption: 72 GitHub stars
- Stars/forks activity: 72 stars, 0 forks; issue activity unavailable in current metadata
- Permission surface: shell or command execution, filesystem or document access
- No real agent outcome reports yet
- Human review required before unattended installation
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Promising candidate for agent workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Use this skill in these scenarios
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Workflow fit
Add it to a complete workflow
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Compare before you install
Similar skills that may fit this task.
Last30days Skill
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Academic Research Skills
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GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Overview
--- name: repo-context-ledger description: Maintain durable, evidence-based repository context whenever an agent initializes a repository, implements or fixes behavior, refactors code, changes an interface, checkpoints or switches tasks, resumes or hands work to another AI tool, collaborates across parallel task sessions, Git branches, or worktrees, prepares a pull request, or completes a coding task. Use this skill to bridge Codex, Claude, Cursor, GitHub Copilot, Grok, and other coding agents through native instruction adapters, private session-isolated handoff drafts, atomic completed-change publication, a shared Context Manifest, language-aware Context Packs, stable feature specifications, verified change history, coverage gates, and managed README summaries without asking the user to run bookkeeping commands. ---
# Repo Context Ledger
Keep repository knowledge current across AI tools and fresh conversation windows. Treat semantic documentation as part of completing code work, while using the bundled deterministic runtime for paths, native adapters, the Context Manifest, indexes, links, README blocks, and validation. Never attempt to read or synchronize private vendor Memory; promote only code-verified facts into Git-tracked context.
## Locate the runtime
Resolve the directory containing this `SKILL.md`. The bundled runtime is `scripts/ledger.py` relative to that directory.
After initialization, prefer the repository-local copy:
```text python .context-ledger/ledger.py <command> ```
Use `python3` instead of `python` when that is the available interpreter.
`--repo` is optional. If omitted, the runtime walks up from the current directory to the nearest `.context-ledger/config.json`, and stops at a nested Git repository boundary.
## Choose the shortest path
Do not run the full lifecycle for every request.
- **Read-only understanding**: `context --query "<task>"`, then `focus --feature "<feature>"`. Do not `start` a session. - **Single-task small fix**: `status` → `start --feature` → implement → `verify -- <command>` → `finish --spec`. `finish` records evidence automatically when this is the only session. If the worktree is large or another session exists, pass `evidence --path`. - **Parallel tasks**: pass `--session <id>` on every lifecycle command. Capture evidence with repeated `--path` values for only this task. - **Medium or large change**: also refresh the related Context Pack, update the stable spec, and write Before/After evidence before `finish`.
`context` returns one primary Context Pack, its linked specs, and why it was chosen. Read that Pack's load order before scanning the rest of the repository.
## Initialize a repository
When the user asks to initialize, adopt, or configure repository context documentation:
1. Run `python <skill-dir>/scripts/ledger.py --repo <repository-root> init --dry-run` and inspect the exact planned files, managed blocks, migrations, and detected modules. The preview must remain read-only. 2. If the plan matches the user's requested repository scope, run the same command without `--dry-run`. Do not hand-recreate or selectively replay the plan. 3. Inspect the generated `.context-ledger/config.json`, detected modules, and existing documentation. 4. Run `python .context-ledger/ledger.py adapters check` and `python .context-ledger/ledger.py manifest check` to confirm native entry files and the shared route index are current. 5. Set `quality.language` (`auto`, `en`, or `zh-CN`) and `quality.detail` (`concise`, `standard`, or `detailed`) only when the repository needs a non-default policy. 6. Preserve existing `AGENTS.md`, `CLAUDE.md`, `.github/copilot-instructions.md`, README content, and documentation. Only managed blocks or the dedicated Cursor adapter may be regenerated. 7. Treat nested Git repositories and worktrees as discovery boundaries. When adopting legacy `docs/changes/YYYY-MM/...` trees, preserve and reuse an existing monthly `index.md`; remove an obsolete index only when the runtime can reproduce the whole file byte-for-byte from current sibling records. 8. Summarize what was added. Do not require the user to learn internal lifecycle commands.
Read [document-model.md](references/document-model.md) when choosing where information belongs or migrating an existing documentation layout.
## Complete behavior-changing work
Apply this workflow autonomously when code behavior changes. Follow [Choose the shortest path](#choose-the-shortest-path). Do not ask the user to run ledger commands.
1. Run `python .context-ledger/ledger.py status`. Reuse only this task's private draft. Never adopt, pause, publish, or rewrite another task's draft. 2. Resolve the record language. Keep code identifiers in source form. 3. If this task will change behavior and has no session, `start --title "<title>" --feature "<feature>"`. Keep the session ID. When more than one task is active, pass `--session <id>`; omission must fail. 4. Route context, then read the primary Pack and its specs:
```text python .context-ledger/ledger.py context --query "<feature, interface, or module>" python .context-ledger/ledger.py focus --feature "<feature>" ```
If no Context Pack exists, create one with `pack --feature`, fill every semantic section, then focus it. 5. Implement the change. Record every claimed check with `verify --session <id> -- <command>`. Failed output is stored as a redacted failure capsule, never as a raw log. Persisted verification evidence replaces repository, Codex, temporary, and user-home roots with stable placeholders, including JSON-escaped Windows paths. If verification is unavailable, use `verify --not-run --reason "<substantive reason>"`. 6. For a small single-session fix, `finish` can collect evidence. If another session exists, or automatic collection finds too many implementation paths, run `evidence --path` for only this task. Read [.context-ledger/writing-quality.md](.context-ledger/writing-quality.md) and remove every `TODO`. Code paths may cite `file.go::Symbol`; the path part is matched against evidence. 7. On medium or large changes, refresh every related Context Pack after tracked production paths change, and update the stable spec when current behavior or contracts changed. 8. Finish with `finish --spec docs/specs/<feature>.md`, or `finish --no-spec --reason "<why>"`. `finish` validates only this session. 9. Run `check --strict --coverage` at integration or pull-request time, not to unblock a parallel session.
## Bridge native Agent entry points
Treat `docs/ai/`, `docs/specs/`, and `docs/changes/` as the vendor-neutral source. `AGENTS.md`, `CLAUDE.md`, `.cursor/rules/repo-context-ledger.mdc`, and `.github/copilot-instructions.md` are thin adapters only.
- Run `python .context-ledger/ledger.py adapters sync` after changing adapter policy or upgrading the runtime. - Run `python .context-ledger/ledger.py adapters check` before completion. - Run `python .context-ledger/ledger.py manifest sync` on the default branch when source documents were repaired manually; normal initialization and derived sync regenerate it automatically. - Prefer code and executed tests over stable specs, stable specs over Context Packs, and all Git-tracked ledger documents over private Agent Memory.
Active lifecycle commands leave formal change history, shared README blocks, and monthly indexes unchanged. `finish` publishes one completed change file; feature branches continue to defer shared derived indexes until merge.
## Collaborate through Git
The runtime supports multiple private task drafts in one worktree. It isolates bookkeeping only: it does not copy source files, create worktrees, claim paths, lock code, or merge code. In a shared worktree, each session records an explicit evidence path set and `finish` ignores unrelated session dirt. Leave source-edit concurrency and conflicts to the host Agent and Git.
Never send messages, delegations, follow-up prompts, or steering instructions to another user-owned task/thread unless the user explicitly requests cross-task coordination. The presence of another session, a foreign stale Pack, a failed global check, or a shared worktree is not permission to contact, pause, redirect, or interrupt it. Report an integration-stage conflict to the user without steering the other task.
Before opening or updating a pull request:
1. Fetch or otherwise update the intended base branch. 2. Run `python .context-ledger/ledger.py team-check --base <base-ref>`. 3. Resolve reported overlaps in code paths or feature handoffs with the other contributor. Rebase or merge the current base as appropriate, then refresh any stale Context Pack. 4. Run `python .context-ledger/ledger.py check --strict`.
After changes are merged, run this once on the configured default branch:
```text python .context-ledger/ledger.py sync --derived ```
This deterministically rebuilds monthly change indexes and managed root/module README summaries from committed source documents. Do not hand-edit generated indexes.
## Switch or resume context
Interpret natural-language requests such as "pause this and fix login," "continue the previous withdrawal task," or "hand this to another AI" as lifecycle instructions. Do not require command syntax from the user.
Before switching away from active work, record an accurate resume summary and concrete next step:
```text python .context-ledger/ledger.py checkpoint --summary "<completed work and current state>" --next "<next concrete action>" python .context-ledger/ledger.py pause --summary "<completed work and current state>" --next "<next concrete action>" ```
Use `checkpoint --session <id>` when another Agent or window will continue the same active task. Use `pause --session <id>` only when suspending that task; never manipulate another task's session.
Focus the target feature's Context Pack, then start its handoff when code behavior will change. Never abandon a different active handoff silently.
Resume the only paused task when it is unambiguous:
```text python .context-ledger/ledger.py resume ```
Resume a selected task when multiple sessions are paused:
```text python .context-ledger/ledger.py resume --session <id> ```
After resuming, read the handoff's resume fields, load its Context Pack, inspect dirty paths, and revalidate warnings about changed commits or stale fingerprints before editing code.
## Handle non-behavior work
For read-only analysis, questions, formatting-only edits, or tasks that do not change repository behavior, do not create a handoff. Read existing context as needed and leave the ledger unchanged.
## Recovery
- Run `python .context-ledger/ledger.py status` to inspect the current state. - Reuse an active draft only when its session ID belongs to the current task. - Start a separate private draft rather than pausing or overwriting another task. - When another session exists, capture evidence with repeated `--path` values for this task only; never adopt the entire shared dirty set. - Use `status` and `--session` lifecycle targeting; do not find or edit the Git-metadata state file manually. - Refresh a stale Context Pack with `pack` after inspecting the changed files. - Repair drifted native entry files with `adapters sync`; never copy private Agent Memory into the ledger as an unverified fact. - Run `python .context-ledger/ledger.py sync` after manually repairing documents or configuration. Add `--derived` on the default branch after merges.
## Writing rules
- Apply [writing-quality.md](references/writing-quality.md) to `evidence-v1` records. Preserve legacy records unless explicitly upgrading them. - Record current truth in `docs/specs/`, chronological evidence in `docs/changes/`, and minimal loading routes in Context Packs. - Keep unfinished drafts private. Publish each completed change into its own file and let the runtime build monthly indexes. - Keep the runtime-generated handoff ID, actor, and branch metadata. Unique filenames are intentional a
Technical details
- Version
- 1.0.0
- License
- MIT
- Last updated
- Aug 21, 2026
- Published
- Aug 21, 2026
Decision snapshot
Fallback candidate
recent repository activity
Audit
Install review
Install and adoption review
- Security
- 78/100
- Maintenance
- 100/100
- Install
- 92/100
Agent-proven evidence
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
- Success rate
- —
- Recent failure
- —
- Outcomes
- 0
- Output quality
- —
- Failed
- 0
- Not relevant
- 0
- Installs
- 0
- Risk blocked
- 0
- Setup needed
- 0
- Production
- 0
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Add to agent workflow
Free and open source. Review the report before installing into production agents.
Growth loop
Share kit
Scenario-led draft for repo-context-ledger, ready for a manual X post.
repo-context-ledger: Maintain durable, evidence-based repository context whenever an agent initializes a repositor... 72 stars https://www.openagentskill.com/skills/gviiisen-repo-context-ledger?ref=x
Optional reply with install command
Listing + install path for repo-context-ledger: https://www.openagentskill.com/skills/gviiisen-repo-context-ledger?ref=x Install: npx skills add gviiisen/repo-context-ledger --skill repo-context-ledger
Listing source
Registry indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- gviiisen
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This Registry indexed listing is attributed to gviiisen but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Add the evidence badges to your README
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/gviiisen-repo-context-ledger)
[](https://www.openagentskill.com/skills/gviiisen-repo-context-ledger)
[](https://www.openagentskill.com/skills/gviiisen-repo-context-ledger/audit)
[](https://www.openagentskill.com/skills/gviiisen-repo-context-ledger)Author
gviiisen
@gviiisen
Tags
Platform fit
Health signals
- GitHub stars
- 72
- Quality score
- 36/100
- Last GitHub push
- Aug 21, 2026
- Framework hints
- Unknown
- OpenAgentSkill views
- 8
- Install copies
- 0
- Outbound clicks
- 0
Community signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & safety
Sandbox only
- GitHub adoption72 GitHub starsCHECK
- Stars/forks activity72 stars, 0 forks; issue activity unavailable in current metadataCHECK
- Recent maintenance1d since pushPASS
- License clarityMITPASS
- README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
- Dependency/runtime risknetwork or browser surfacePASS
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