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,
Asset-Profil
Recherche und Wissensarbeit
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Szenario
Recherche-Agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent-Fit
Claude Code + OpenAI Agents + Cursor
Geeignet für Codex, Claude Code, Cursor, CLI oder benutzerdefinierte Agents.
Installieren
Bereit
npx skills add gviiisen/repo-context-ledger --skill repo-context-ledger
Wartung
Aktuell
1 Tage seit dem letzten Push
Risiko
Riskant
Permission surface may require sandboxing
GitHub-Qualität
72
65/100 Qualität · 69/100 Vertrauen
Abdeckungs-Tags
Review-Notizen
Permission surface may require sandboxing · Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
Agent-Adoptionskarte
Vertrauen, Audit und Installationsbereitschaft auf einen Blick
Diese Werte kombinieren öffentliche Repository-Metadaten, OpenAgentSkill-Reviewsignale, Wartungsaktualität und Installationsbereitschaft. Sie helfen bei der Vorauswahl, ersetzen aber keine menschliche Prüfung.
Qualität
VielversprechendUseful candidate, but compare it with alternatives before adopting.
Vertrauen
Nur SandboxNützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.
Audit
RiskantMaschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
OpenAgentSkill Trust Score v5
Nur Sandbox
Nur in einer Sandbox ausführen und nahe Alternativen vergleichen, bevor sie produktiv eingesetzt wird.
Stars
72 GitHub-Stars
Repository-Aktivität
72 Stars und 0 Forks
Wartung
1 Tage seit dem letzten Push
Lizenz
MIT
Installieren
npx skills add gviiisen/repo-context-ledger --skill repo-context-ledger
Installationssicherheit
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsfläche
shell or command execution, filesystem or document access
Agent-Ergebnisse
Noch keine Agent-Ergebnisdaten
Dokumentation
Starker README/SKILL.md-Kontext
Risikoübersicht
Vor Produktion prüfen
- 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
Installationsbereitschaft
Installationspfad verfügbar
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Lizenz ist angegeben
- Noch keine Agent-Proven-Ergebnisbelege
Agent-lesbare Metadaten
Maschinenlesbare Entscheidungsdaten für diesen Skill.
Nutze diesen Block oder das eingebettete JSON, um zu entscheiden, ob ein Agent diesen Skill installieren, eine Alternative wählen oder zuerst menschliche Prüfung anfordern soll.
Geeignete Aufgaben
- Research-Agent-Workflows
- Claude-Code-Teams
- builders willing to evaluate younger projects
- Suchquellen
Geeignete Agents
Installationsentscheidung
- Befehl
- npx skills add gviiisen/repo-context-ledger --skill repo-context-ledger
- Richtlinie
- Blockieren
- Menschliche Prüfung
- Ja
Vertrauen und Risiko
- Vertrauen
- 61/100
- Audit
- 76/100
- Risikoebene
- Riskant
Ergebnis-Loop
- Endpoint
- /api/agent/outcome
- Event-ID
- resolve
- Ergebnisse
- 5
Installationsbefehl
npx skills add gviiisen/repo-context-ledger --skill repo-context-ledgerNicht verwenden, wenn
- Teams, die ein vom Anbieter unterstütztes SLA benötigen
- 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
- Hinweise auf Hochrisiko-Berechtigungen: Shell- oder Befehlsausführung
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
Alternative
DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent-Sicherheit v2
40/100 · Automatische Installation vermeiden
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.
Hoch
Shell- oder Befehlsausführung
Die Skill-Metadaten verweisen auf Terminal-, CLI-, Shell-, Subprozess- oder Befehlsausführungs-Workflows.
Mittel
Browser automation
Skill may drive a browser or interact with web pages.
Mittel
Netzwerkzugriff
Die Skill ruft wahrscheinlich Remote-Seiten, APIs, Repositories oder externe Dienste ab.
Mittel
Dateisystemzugriff
Die Skill kann Projektdateien, Dokumente, generierte Artefakte oder den lokalen Arbeitsbereich lesen oder schreiben.
- Audit risk risky exceeds max_risk=medium
- Hinweise auf Hochrisiko-Berechtigungen: Shell- oder Befehlsausführung
- Permission surface may require sandboxing
Installationsziele
Diesen Skill im Agent-Workflow installieren
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
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-Auflösungsplan
Lass einen Agent die Eignung vor der Installation prüfen.
Die Resolve API liefert die beste Skill, Alternativen, Sicherheitsrichtlinien, Auditnotizen, Installationsziel und einen direkt nutzbaren Prompt.
JSON öffnen
/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
Installationsübergabe
/api/skills/gviiisen-repo-context-ledger/install
Agent sollte prüfen
- 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.
Prompt kopieren
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-Übergabe
Gib dem Agent den Installationspfad, nicht noch ein Verzeichnis.
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
Installationsübergabe
/api/skills/gviiisen-repo-context-ledger/install
LLM-Textformat
/api/skills/gviiisen-repo-context-ledger/install?format=text
Alternativen finden
/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-Metadaten
Agent-lesbares Profil für die automatische Skill-Auswahl.
Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.
Manifest
/api/registry/manifest/gviiisen-repo-context-ledger
LLM-Text
/api/registry/manifest/gviiisen-repo-context-ledger?format=text
Installationsalias
/api/registry/install/gviiisen-repo-context-ledger
Empfehlen
/api/registry/recommend?task=Use%20repo-context-ledger%20in%20an%20agent%20workflow&limit=3
Agent-Fit
Recherche-Agents
Use-Case-Tags
Plattformen
Claude Code, OpenAI Agents, Cursor
Audit-Bericht
Riskant · 76/100
Maschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
Agent-Entscheidungspanel
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Rolle im Stack
Fallback-Kandidat
Primäre Eignung
Recherche-Agents
Vertrauenslabel
Zuerst prototypisieren
Installationspfad
Befehl bereit
Verwenden wenn
- Research-Agent-Workflows
- Claude-Code-Teams
- builders willing to evaluate younger projects
Evidenz
- recent repository activity
- install command or GitHub repo available
- Qualitätsprofil 65/100
- 9 OpenAgentSkill-Interaktionen
zuerst prüfen
- The SKILL.md excerpt is truncated, but the provided content is sufficient for evaluation.
Implementierungspfad
- 1Installieren Sie es in einem Sandbox-Agent und führen Sie eine Recherche-Agents-Aufgabe vollständig aus.
- 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.
Vertrauensprofil
Nur Sandbox
Nützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.
GitHub-Akzeptanz
Prüfen72 GitHub-Stars
Star-/Fork-Aktivität
Prüfen72 Stars und 0 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
Bestanden1 Tage seit dem letzten Push
Lizenzklarheit
BestandenMIT
Positive Signale
- KI-Prüfung genehmigt
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Kürzlich gewartetes Repository
- Der Installationsbefehl weist kein offensichtliches Hochrisikomuster auf
- Ergebniszyklus ist bereit, benötigt aber den ersten echten Agent-Lauf
Vor Installation prüfen
- 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
- Noch keine echten Agent-Ergebnisberichte
- Vor unbeaufsichtigter Installation ist menschliche Prüfung erforderlich
Empfohlene Aktion
Nur in einer Sandbox ausführen und nahe Alternativen vergleichen, bevor sie produktiv eingesetzt wird.
Qualitätsprofil
Vielversprechend Kandidat für Agent-Workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow-Eignung
Diese Skill in diesen Szenarien nutzen
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-Eignung
Zum vollständigen Workflow hinzufügen
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.
Alternativen-Shortlist
Vor Installation vergleichen
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Übersicht
--- 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
Technische Details
- Version
- 1.0.0
- Lizenz
- MIT
- Letzte Aktualisierung
- 21. Aug. 2026
- Veröffentlicht
- 21. Aug. 2026
Entscheidungsübersicht
Fallback-Kandidat
recent repository activity
Audit
Installationsprüfung
Installations- und Adoptionsprüfung
- Sicherheit
- 78/100
- Wartung
- 100/100
- Installieren
- 92/100
Von Agent belegte Evidenz
Von Agent belegte Evidenz
Ergebnisberichte nach Resolve, Prüfung, Installation und einem begrenzten Lauf.
- Erfolgsrate
- —
- Letzter Fehler
- —
- Ergebnisse
- 0
- Ausgabequalität
- —
- Fehlgeschlagen
- 0
- Nicht relevant
- 0
- Installationen
- 0
- Durch Risiko blockiert
- 0
- Einrichtung erforderlich
- 0
- Produktion
- 0
Noch keine Agent-Ergebnisdaten. Der erste Lauf kann Erfolg, Einrichtungsbedarf, Risikoblockaden, Fehler oder Irrelevanz über /api/agent/outcome melden.
Installieren
Zum Agent-Workflow hinzufügen
Kostenlos und Open Source. Bericht vor der Installation in Produktions-Agents prüfen.
Wachstums-Loop
Share-Kit
Szenariobasierter Entwurf für repo-context-ledger, bereit für einen manuellen 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
Optionale Antwort mit Installationsbefehl
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
Quelle des Eintrags
Registry-indexiert
Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.
- Ersteller
- gviiisen
- Indexiert von
- OpenAgentSkill Community-Index
Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.
Diesen Skill beanspruchenEigentümeranspruch
Diesen Skill-Eintrag beanspruchen
Dieser Registry-indexiert-Eintrag wird gviiisen zugeschrieben, ist aber noch nicht offiziell markiert. Beanspruche ihn, um ein verifiziertes Eigentümersignal hinzuzufügen und künftige Launch-, Installations- und Audit-Updates vertrauenswürdiger zu machen.
Creator-Backlink-Kit
Evidenz-Badges in deine README einfügen
Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.
[](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)Autor
gviiisen
@gviiisen
Tags
Plattform-Fit
Gesundheitssignale
- GitHub-Stars
- 72
- Qualitätswert
- 36/100
- Letzter GitHub-Push
- 21. Aug. 2026
- Framework-Hinweise
- Unbekannt
- OpenAgentSkill-Aufrufe
- 9
- Installationskopien
- 0
- Externe Klicks
- 0
Community-Signal
Teile mit, ob dieser Skill für deinen Agent-Workflow nützlich ist. Zusammengefasstes Feedback verbessert das Ranking im Laufe der Zeit.
Vertrauen & Sicherheit
Nur Sandbox
- GitHub-Akzeptanz72 GitHub-StarsPrüfen
- Star-/Fork-Aktivität72 Stars und 0 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbarPrüfen
- Aktuelle Wartung1 Tage seit dem letzten PushBestanden
- LizenzklarheitMITBestanden
- README/SKILL.md-VollständigkeitMetadaten enthalten ausreichend Nutzungs- und Workflow-KontextBestanden
- Abhängigkeits-/Laufzeitrisikonetwork or browser surfaceBestanden
Ähnliche Skills
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
53.5K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsDeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
19.8K Stars