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hivemind-graph

Prix non confirmé★ 1,593 Stars GitHubRegistre mis à jour · 2 sept. 2026agent-skill

Vue d’ensemble

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).

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Documentation source, pas des instructions pour ce site. Vérifiez les permissions avant d’exécuter des commandes.

Hivemind Code Graph

A deterministic, AST-derived map of the current repository — every function, class, method, interface, type, enum, const, and module, plus the edges between them (calls, imports, extends, implements, method_of). It is queried as synthesized files under the Deeplake mount; there are no real files on disk and no network call in the read path.

The graph builds and refreshes automatically (on Stop / SessionEnd, gated by a rate limit + git diff). You never run a build command — just read it.

Use it as a fast INDEX to locate the few files/symbols that matter, then open them with Read to answer. It is not a substitute for the source.

When to use this skill

Activate when the user asks a structural / relational question about the code:

"What calls pushSnapshot?" / "Who uses this function?"
"What does deeplake-pull.ts import?" / "What depends on X?"
"Where is GraphSnapshot defined?" / "Find the function that handles Y."
"What are the main subsystems / the architecture here?"
"If I change this signature, what's affected?" → use impact/<symbol> (transitive blast radius)

When NOT to use this skill

Reading the body of a symbol you already located → use Read on the real source file. The graph gives location + relationships, not full source.
Code that isn't committed/built yet — the graph can lag uncommitted edits. If a file's mtime is newer than the build timestamp, read the live source.
Languages outside TypeScript, JavaScript, and Python (Go, Rust, …) — the extractor covers those three, with cross-file calls/imports resolved for named imports. For anything else, fall back to grep/read.

Path cheat sheet

cat ~/.deeplake/memory/graph/index.md
#   Overview: node/edge counts, kind breakdown, top files by node count.

cat ~/.deeplake/memory/graph/query/<pattern>   # START HERE (the 2-in-1)
#   Search + expand the top matches with their 1-hop neighbors (callers,
#   callees, imports, heritage). Multi-token AND: query/<a>+<b>.

cat ~/.deeplake/memory/graph/find/<pattern>
#   Case-insensitive substring search on node id + label (max 50 hits).
#   Prints numbered handles [1] [2] ... saved for this worktree.

cat ~/.deeplake/memory/graph/show/<handle-or-pattern>
#   <handle>: a digit from a prior find/ (e.g. 3).
#   <pattern>: a substring → unique node detail, or a candidate list.
#   Output: the node + its 1-hop neighbors grouped by edge relation.

cat ~/.deeplake/memory/graph/neighborhood/<file>
#   Every symbol in a file + its cross-file neighbors (callers/callees/imports).

cat ~/.deeplake/memory/graph/impact/<pattern>
#   Transitive dependents — the blast radius of changing a symbol.

cat ~/.deeplake/memory/graph/path/<from>/<to>
#   Shortest dependency path between two symbol patterns (trace a flow across files).

cat ~/.deeplake/memory/graph/layers      # architectural layers / subsystems
cat ~/.deeplake/memory/graph/tour        # deterministic guided walkthrough

Workflow

Broad? Start at index.md to see subsystems and the biggest files.
Looking for a symbol? find/<name> (or query/<name>) → pick the handle.
Want relationships? show/<handle> / neighborhood/<file> → callers/callees, imports.
Tracing a flow? path/<from>/<to>. Change impact? impact/<symbol>.
Need the actual code? Take the source_file:line and Read it — don't answer from the graph alone.

Anti-patterns (read these)

"Incoming (0)" does NOT mean dead code. Cross-file calls are resolved for named imports (TS/JS/Python), but instance-method dispatch (obj.method()), dynamic calls, and nested/inner functions are NOT — a zero-incoming symbol may still be reached via one of those. Confirm in the source before calling it unused.
The graph can be stale. It rebuilds at most once per rate-limit window. The SessionStart inject prints the build age; if it's old or you've just edited a file, prefer the live source for that file.
Don't try to build it. There is no user-facing build step in normal use; the hooks handle it. Just read the mount.
find/ is lexical, not semantic. It matches substrings, not meaning — find/auth won't surface login/credentials unless those strings appear in the id/label. Try multiple keywords if the first misses.

Voir la source ↗

Métadonnées du fichier

name: hivemind-graph
description: Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).
allowed-tools: Read Bash

Voir le texte original

---
name: hivemind-graph
description: Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).
allowed-tools: Read Bash
---

# Hivemind Code Graph

A deterministic, AST-derived map of the current repository — every function,
class, method, interface, type, enum, const, and module, plus the edges between
them (`calls`, `imports`, `extends`, `implements`, `method_of`). It is queried as
synthesized files under the Deeplake mount; there are no real files on disk and
no network call in the read path.

The graph **builds and refreshes automatically** (on Stop / SessionEnd, gated by
a rate limit + git diff). You never run a build command — just read it.

Use it as a fast **INDEX** to locate the few files/symbols that matter, then open
them with `Read` to answer. It is not a substitute for the source.

## When to use this skill

Activate when the user asks a *structural / relational* question about the code:

- "What calls `pushSnapshot`?" / "Who uses this function?"
- "What does `deeplake-pull.ts` import?" / "What depends on X?"
- "Where is `GraphSnapshot` defined?" / "Find the function that handles Y."
- "What are the main subsystems / the architecture here?"
- "If I change this signature, what's affected?" → use `impact/<symbol>` (transitive blast radius)

## When NOT to use this skill

- Reading the **body** of a symbol you already located → use `Read` on the real
  source file. The graph gives location + relationships, not full source.
- Code that isn't **committed/built** yet — the graph can lag uncommitted edits.
  If a file's mtime is newer than the build timestamp, read the live source.
- Languages outside **TypeScript, JavaScript, and Python** (Go, Rust, …) — the
  extractor covers those three, with cross-file `calls`/`imports` resolved for
  named imports. For anything else, fall back to grep/read.

## Path cheat sheet

```bash
cat ~/.deeplake/memory/graph/index.md
#   Overview: node/edge counts, kind breakdown, top files by node count.

cat ~/.deeplake/memory/graph/query/<pattern>   # START HERE (the 2-in-1)
#   Search + expand the top matches with their 1-hop neighbors (callers,
#   callees, imports, heritage). Multi-token AND: query/<a>+<b>.

cat ~/.deeplake/memory/graph/find/<pattern>
#   Case-insensitive substring search on node id + label (max 50 hits).
#   Prints numbered handles [1] [2] ... saved for this worktree.

cat ~/.deeplake/memory/graph/show/<handle-or-pattern>
#   <handle>: a digit from a prior find/ (e.g. 3).
#   <pattern>: a substring → unique node detail, or a candidate list.
#   Output: the node + its 1-hop neighbors grouped by edge relation.

cat ~/.deeplake/memory/graph/neighborhood/<file>
#   Every symbol in a file + its cross-file neighbors (callers/callees/imports).

cat ~/.deeplake/memory/graph/impact/<pattern>
#   Transitive dependents — the blast radius of changing a symbol.

cat ~/.deeplake/memory/graph/path/<from>/<to>
#   Shortest dependency path between two symbol patterns (trace a flow across files).

cat ~/.deeplake/memory/graph/layers      # architectural layers / subsystems
cat ~/.deeplake/memory/graph/tour        # deterministic guided walkthrough
```

## Workflow

1. Broad? Start at `index.md` to see subsystems and the biggest files.
2. Looking for a symbol? `find/<name>` (or `query/<name>`) → pick the handle.
3. Want relationships? `show/<handle>` / `neighborhood/<file>` → callers/callees, imports.
4. Tracing a flow? `path/<from>/<to>`. Change impact? `impact/<symbol>`.
5. Need the actual code? Take the `source_file:line` and `Read` it — don't answer from the graph alone.

## Anti-patterns (read these)

- **"Incoming (0)" does NOT mean dead code.** Cross-file `calls` are resolved for
  *named imports* (TS/JS/Python), but **instance-method dispatch** (`obj.method()`),
  dynamic calls, and nested/inner functions are NOT — a zero-incoming symbol may
  still be reached via one of those. Confirm in the source before calling it unused.
- **The graph can be stale.** It rebuilds at most once per rate-limit window. The
  SessionStart inject prints the build age; if it's old or you've just edited a
  file, prefer the live source for that file.
- **Don't try to build it.** There is no user-facing build step in normal use;
  the hooks handle it. Just read the mount.
- **`find/` is lexical, not semantic.** It matches substrings, not meaning —
  `find/auth` won't surface `login`/`credentials` unless those strings appear in
  the id/label. Try multiple keywords if the first misses.

Examiner la source

Prix et coûts d’utilisation

Obtenir le skill: Prix non confirmé
L’utiliser: Prérequis non confirmés. Consultez les frais d’agent, d’API et de services à la source.
Licence: Apache-2.0
Prix non confirmé: Le prix n’est pas confirmé. Les liens existants vers les sources et l’installation restent disponibles.

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Source du skill enregistrée

Un chemin vers les instructions est enregistré. Cela ne constitue pas un test, une garantie de sécurité ou de compatibilité.

Réviser avant installation: Éviter l’installation automatique

Licence: Apache-2.0

Dependency or permission surface needs review
Permission surface may require sandboxing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Ouvrir l’audit complet

Les outils sont des indications de métadonnées, pas une compatibilité testée. Les prompts sont des suggestions.

Commencer par une petite tâche

1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.

Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.

Source et conseils d’utilisation

Répertorié

Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source: activeloopai/hivemind
Licence: Apache-2.0
Version: 1.0.0
Dernier push GitHub: 2 sept. 2026
Registre mis à jour: 2 sept. 2026
Chemin des instructions: harnesses/claude-code/skills/hivemind-graph/SKILL.md @ 916eb4110c23

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

76/100

Solide

Confiance

67/100

Sandbox uniquement

Audit

79/100

Revue nécessaire

Ouvrir l’audit complet Voir le rapport d’évaluation

Dependency or permission surface needs review
Permission surface may require sandboxing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
Résultats: —

Copier ne signifie pas installer. Les compteurs nécessitent un rapport de réussite et ne garantissent pas la qualité globale.

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Plus de détails

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    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "activeloopai-hivemind-graph",
      "task": "Use hivemind-graph in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/activeloopai-hivemind-graph",
    "api": "https://www.openagentskill.com/api/agent/skills/activeloopai-hivemind-graph",
    "audit": "https://www.openagentskill.com/skills/activeloopai-hivemind-graph/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=activeloopai-hivemind-graph&task=Use%20hivemind-graph%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20hivemind-graph%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20hivemind-graph%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/activeloopai-hivemind-graph/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/activeloopai-hivemind-graph"
  }
}

Pour le créateur

Source de la fiche

Indexé par Registry

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Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.

Créateur: activeloopai
Source: activeloopai/hivemind
Indexé par: Index communautaire OpenAgentSkill

L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.

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Cette fiche Indexé par Registry est attribuée à activeloopai, mais n’est pas encore marquée officielle. Revendiquez-la pour ajouter un signal de propriétaire vérifié et rendre les futures mises à jour de lancement, d’installation et d’audit plus fiables.

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