Cognee:recall Agent Skill

Semantic and graph search across Cognee knowledge graph. Queries project memory, finds related entities and decisions, injects results as agent context. Triggers on: 'cognee recall', 'search memory', 'what do we know about', 'find related', 'graph search', 'memory search', 'recall context'.

2k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

196

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/coco-research/coco --skill cognee:recall

The instruction itself

15 sections, as written by the author

/cognee-recall — Search & Recall from Knowledge Graph

Semantic, graph-traversal, and lexical search across Cognee's knowledge graph. Finds entities, decisions, events, and their relationships — then injects relevant results as agent context for informed decision-making.

Quick Reference

COGNEE="${COGNEE_BASE_URL:-http://localhost:8000}"
DATASET="my-project"

# Semantic search (auto-selects best strategy)
curl -s -X POST "$COGNEE/api/v1/search" \
  -H "Content-Type: application/json" \
  -d '{"query": "authentication decisions", "datasets": ["my-project"], "search_type": "FEELING_LUCKY", "top_k": 10}' | jq .

# Graph completion search (relationship-aware)
curl -s -X POST "$COGNEE/api/v1/search" \
  -H "Content-Type: application/json" \
  -d '{"query": "who reports to Alice", "datasets": ["my-project"], "search_type": "GRAPH_COMPLETION", "top_k": 10}' | jq .

# Recall with context injection (adds system prompt)
curl -s -X POST "$COGNEE/api/v1/recall" \
  -H "Content-Type: application/json" \
  -d '{"query": "rate limiting", "datasets": ["my-project"], "top_k": 10, "only_context": true}' | jq .

# Cross-project search
curl -s -X POST "$COGNEE/api/v1/search" \
  -H "Content-Type: application/json" \
  -d '{"query": "auth decisions", "datasets": ["project-a", "project-b", "project-c"], "search_type": "FEELING_LUCKY"}' | jq .

Search Types

Cognee supports multiple search strategies. Use FEELING_LUCKY for auto-selection (recommended), or specify one:

| Type | Best for |

|------|---------|

| FEELING_LUCKY | Auto-selects best strategy (default, recommended) |

| GRAPH_COMPLETION | Relationship-heavy queries ("who owns X", "what depends on Y") |

| GRAPH_COMPLETION_COT | Complex reasoning with chain-of-thought |

| GRAPH_COMPLETION_CONTEXT_EXTENSION | Expanding context around a node |

| GRAPH_SUMMARY_COMPLETION | Summarization of graph neighborhood |

| RAG_COMPLETION | Retrieval-augmented generation |

| TRIPLET_COMPLETION | Entity-relationship-entity patterns |

| CHUNKS | Raw chunk retrieval |

| CHUNKS_LEXICAL | Keyword/lexical matching |

| SUMMARIES | Pre-computed summaries |

| NATURAL_LANGUAGE | Free-form natural language queries |

| TEMPORAL | Time-based queries |

| CODING_RULES | Code-specific patterns |

Sub-commands

/cognee-recall search — Run a semantic/graph search

Procedure:

Ask the user what they're looking for (or use the provided query).
Determine the best search type based on the query:
Queries about relationships → GRAPH_COMPLETION
General "what do we know" → FEELING_LUCKY
Time-based ("last week", "in Q2") → TEMPORAL if available
Code-related → CODING_RULES
Detect which datasets to search:
Default: current project dataset
If user mentions another project: include its dataset
Use /cognee status to list available datasets
Execute search:

COGNEE="${COGNEE_BASE_URL:-http://localhost:8000}"

curl -s -X POST "$COGNEE/api/v1/search" \
  -H "Content-Type: application/json" \
  -d "{
    \"query\": \"$QUERY\",
    \"datasets\": $DATASETS_JSON,
    \"search_type\": \"$SEARCH_TYPE\",
    \"top_k\": $TOP_K
  }" | jq .

Present results:

COGNEE RECALL — "$QUERY"
==================================================
Found N results across M datasets

[1] DECISION: Use JWT for API auth (2026-06-30)
    Context: Stateless, works with existing infra
    Dataset: my-project | Score: 0.94

[2] ENTITY: Auth Service — depends_on → PlatformHub
    Description: Authentication and authorization service
    Dataset: my-project | Score: 0.87

[3] TASK: Set up JWT middleware (open, priority 1)
    Assigned to: Alice Chen
    Dataset: my-project | Score: 0.82

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

/cognee-recall context — Inject results as agent context

Same as search, but formats results for direct injection into the agent's context window. Use this before making architectural decisions or when context from past sessions is needed.

Procedure:

Run search as above.
Format results as a compact context block:

[COGNEE CONTEXT INJECTION — {timestamp}]
Query: "{original_query}"
Dataset(s): {dataset_names}

Relevant knowledge:
• DECISION ({date}): {text} — {context} [relevance: {score}]
• ENTITY: {name} ({type}) — {description} [relevance: {score}]
• TASK: {text} ({status}) — assigned to {assignee} [relevance: {score}]
• EVENT: {title} ({date}, {type}) — {summary} [relevance: {score}]

Use this context to inform your response. Cite specific decisions and entities where relevant.

The agent then uses this context transparently in its reasoning.

/cognee-recall graph — Explore entity neighborhood

Explore the graph around a specific entity to understand its relationships.

COGNEE="${COGNEE_BASE_URL:-http://localhost:8000}"

# First, get the dataset ID
DATASET_ID=$(curl -s "$COGNEE/api/v1/datasets" | jq -r '.[] | select(.name=="my-project") | .id')

# Get the full graph
curl -s "$COGNEE/api/v1/datasets/$DATASET_ID/graph" | jq .

Present as a relationship map:

ENTITY GRAPH — "Auth Service" (my-project)
==================================================
                      ┌──────────────────┐
                      │   Auth Service   │
                      │   (system)       │
                      └───┬──────────┬───┘
                          │          │
              depends_on  │          │ owns
                          │          │
                   ┌──────▼──┐  ┌───▼──────────┐
                   │Platform │  │ JWT Middleware│
                   │Hub      │  │ (module)      │
                   │(module) │  └───────────────┘
                   └─────────┘

Related decisions:
  • Use JWT for API auth (2026-06-30) — relates to Auth Service

Related tasks:
  • Set up JWT middleware (open) — assigned to Alice Chen
  • Update API docs (open) — assigned to unassigned

/cognee-recall cross-project — Search across multiple projects

Search for related knowledge across all available datasets.

COGNEE="${COGNEE_BASE_URL:-http://localhost:8000}"

# Get all dataset names
DATASETS=$(curl -s "$COGNEE/api/v1/datasets" | jq -r '[.[].name] | join(",")')

# Cross-project search
curl -s -X POST "$COGNEE/api/v1/search" \
  -H "Content-Type: application/json" \
  -d "{
    \"query\": \"$QUERY\",
    \"datasets\": [$DATASETS_JSON],
    \"search_type\": \"FEELING_LUCKY\",
    \"top_k\": 15
  }" | jq .

Present results grouped by dataset:

CROSS-PROJECT RECALL — "$QUERY"
==================================================
Found N results across M datasets

my-project (5 results):
  [1] DECISION: Use JWT for API auth — 0.94
  [2] ENTITY: Auth Service — 0.87
  ...

e-and-c (3 results):
  [1] DECISION: Stakeholder role for external users — 0.91
  [2] ENTITY: External Review System — 0.84
  ...

optimize (2 results):
  [1] DECISION: Migration to pgvector — 0.78
  ...

Behavior Rules

Proactive recall triggers

Automatically run /cognee-recall search when:

User asks "what do we know about X" or "what did we decide about Y"
User starts a new task that references past work ("continue working on auth")
User makes a decision that might conflict with past decisions
Before architectural or design discussions that would benefit from context

Relevance threshold

Only show results with relevance score > 0.5 by default. If fewer than 3 results exceed threshold, tell the user: "Only {N} low-relevance results found. Try a broader query."

Context injection discipline

Inject context before reasoning about a decision, not after.
Cite specific decisions/entities from the graph in responses: "Based on the June 30 decision to use JWT for API auth [Cognee]..."
Never fabricate — if the graph has no relevant data, say so.

Session-aware recall

If Cognee supports sessions, tag recalls with a session ID for better multi-turn context:

SESSION_ID="coco-$(date +%s)"

curl -s -X POST "$COGNEE/api/v1/search" \
  -H "Content-Type: application/json" \
  -d "{
    \"query\": \"$QUERY\",
    \"datasets\": [\"$DATASET\"],
    \"search_type\": \"FEELING_LUCKY\",
    \"top_k\": 10
  }" | jq .

Fallback Behavior

If Cognee is unreachable:

Check if Brain is available: look for project_brain.db in current or parent directories
If available: "Cognee is not running. Using Brain for this query instead." Run equivalent /brain context --search "query"
If neither available: "No memory backend available. Start Cognee with cognee server start or initialize Brain with /brain init."

Prerequisites

Cognee must be running and the project dataset must exist (created via /cognee init).

# Verify
curl http://localhost:8000/health
curl http://localhost:8000/api/v1/datasets | jq '.[].name'

Other skills for the same job

different authors, same section of the catalogue

Declarative Agents

by github

vendor ×1

Complete development kit for Microsoft 365 Copilot declarative agents with three comprehensive workflows (basic, advanced, validation), TypeSpec support, and Microsoft 365 Agents Toolkit integration

Format and structurally validate local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed professionals. Use for source traceability, clinician-authored intervention records, goals and checkpoints, shared-decision records, reconciliation handoffs, and release gates—not for clinical decision-making.

> provider/change budget/修改卖家/修改预算/draft/草稿/我的任务/my tasks/what am I working on/关闭/取消任务/决策列表/decision list/指定服务商/browse (sender.role = COUNTERPARTY, not you); (3) literal "Read the okx-ai skill" (or legacy "Read the okx-agent-task skill") in the envelope.

57k tokens

Prior Auth Review Skill

by anthropics

vendor ×1

Automate payer review of prior authorization (PA) requests. This skill should be used when users say "Review this PA request", "Process prior authorization for [procedure]", "Assess medical necessity", "Generate PA decision", or when processing clinical documentation for coverage policy validation and authorization decisions.

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.

Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.

Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order.

Structured persuasion for tech leads, PMs, and founders—not activity logs. Five scenarios (kickoff, status update, wrap-up, investor pitch, solution selling) on one 5-part framework (Hook→Context→Proposal→Evidence→Ask). AI prompts for missing materials and audience context; pre-submit checklist. Claude Code plugin; Cursor, Codex, and chat via prompts.

5k tokens

How to use it

Copy the folder

Take coco-research/cognee:recall from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.