Agent skill

aim-github-search

Search GitHub issues, PRs, commits, and CI results with semantic search and filters

View SKILL.md on GitHub Repository
Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/aim-github-search-hidden-history-ai-memory

SKILL.md

Search GitHub - Semantic Search for GitHub Content

Search the discussions collection for GitHub-sourced content using semantic similarity with advanced filtering.

Usage

bash
# Basic semantic search
/aim-github-search "authentication bug"

# Filter by type
/aim-github-search "API refactoring" --type github_pr
/aim-github-search "CI failures" --type github_ci_result

# Filter by state
/aim-github-search "deployment fix" --state merged

# Combine filters
/aim-github-search "security" --type github_issue --limit 10

Options

  • --type <type> - Filter by GitHub document type: github_issue, github_pr, github_commit, github_ci_result, github_code_blob, github_issue_comment, github_pr_review, github_pr_diff
  • --state <state> - Filter by state: open, closed, merged
  • --limit <n> - Maximum results to return (default: 5)

Result Format

Each result includes:

  • GitHub URL - Direct link
  • Metadata badges - Type, State, Date
  • Content snippet - First ~300 characters
  • Relevance score - Semantic similarity with decay (0-100%)

Qdrant Connection Details

GitHub content is stored in the discussions collection:

Parameter Value
Host localhost
Port 26350 (NOT the default 6333)
API Key Required. Read from env: QDRANT_API_KEY
Collection discussions
URL http://localhost:26350

To get the API key:

bash
export QDRANT_API_KEY="$(grep QDRANT_API_KEY ~/.ai-memory/docker/.env | cut -d= -f2)"

Qdrant Payload Schema

Every GitHub point in discussions has the following payload fields. Use these exact names for filtering.

Common Fields (all GitHub points)

Field Type Description Example
content string Composed document text "[PR #42] Add decay scoring..."
type string Document type "github_pr", "github_issue"
source string Always "github" "github"
group_id string owner/repo "Hidden-History/ai-memory"
github_id int Issue/PR number 42
state string Current state "open", "closed", "merged"
url string GitHub URL "https://github.com/..."
github_updated_at string ISO 8601 from GitHub API "2026-02-16T..."
files_changed list[string] Files touched (PRs, commits) ["src/memory/decay.py"]
labels list[string] Issue/PR labels ["bug", "v2.0.6"]
merged_at string or null PR merge timestamp "2026-02-16T..."
is_current bool Versioning: latest version true

Direct Query Examples

Use the curl-to-file-to-python pattern for direct Qdrant queries.

Important: Save curl output to a temp file first, then process with Python. Do NOT pipe directly to python3.

Search by source

bash
# Step 1: Get API key
export QDRANT_API_KEY="$(grep QDRANT_API_KEY ~/.ai-memory/docker/.env | cut -d= -f2)"

# Step 2: Query Qdrant and save to temp file
# Replace "owner/repo-name" with your GITHUB_REPO value (e.g., "Hidden-History/ai-memory")
curl -s -H "Api-Key: $QDRANT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "filter": {
      "must": [
        {"key": "source", "match": {"value": "github"}},
        {"key": "group_id", "match": {"value": "owner/repo-name"}}
      ]
    },
    "limit": 10,
    "with_payload": true
  }' \
  http://localhost:26350/collections/discussions/points/scroll > /tmp/github_results.json

# Step 3: Process with Python
python3 -c "
import json
data = json.load(open('/tmp/github_results.json'))
points = data.get('result', {}).get('points', [])
print(f'Found {len(points)} points')
for p in points:
    pl = p.get('payload', {})
    print(f\"  [{pl.get('type', '?')}] {pl.get('state', '?')} - {pl.get('url', '?')} - {pl.get('content', '')[:80]}...\")
"

Filter by type and state

bash
# Replace "owner/repo-name" with your GITHUB_REPO value
curl -s -H "Api-Key: $QDRANT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "filter": {
      "must": [
        {"key": "source", "match": {"value": "github"}},
        {"key": "group_id", "match": {"value": "owner/repo-name"}},
        {"key": "type", "match": {"value": "github_pr"}},
        {"key": "state", "match": {"value": "merged"}}
      ]
    },
    "limit": 20,
    "with_payload": true
  }' \
  http://localhost:26350/collections/discussions/points/scroll > /tmp/github_results.json

Count GitHub points in collection

bash
# Replace "owner/repo-name" with your GITHUB_REPO value
curl -s -H "Api-Key: $QDRANT_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "filter": {
      "must": [
        {"key": "source", "match": {"value": "github"}},
        {"key": "group_id", "match": {"value": "owner/repo-name"}}
      ]
    },
    "exact": true
  }' \
  http://localhost:26350/collections/discussions/points/count | python3 -c "
import json, sys
data = json.load(sys.stdin)
print(f\"GitHub points: {data.get('result', {}).get('count', 0)}\")
"

Python Implementation Reference

This skill uses the source="github" filter pattern against the discussions collection:

python
# Key filter patterns
from qdrant_client.models import FieldCondition, Filter, MatchValue

must_conditions = [
    FieldCondition(key="source", match=MatchValue(value="github")),
    FieldCondition(key="group_id", match=MatchValue(value=group_id)),
]
if type_filter:
    must_conditions.append(
        FieldCondition(key="type", match=MatchValue(value=type_filter))
    )
if state_filter:
    must_conditions.append(
        FieldCondition(key="state", match=MatchValue(value=state_filter))
    )

Technical Details

  • Semantic Search: Uses jina-embeddings-v2-base-en for vector similarity
  • Tenant Isolation: Mandatory group_id filter prevents cross-repo leakage
  • Performance: < 2s for typical searches
  • Collection: discussions (GitHub content stored alongside conversation data)
  • Score Threshold: Configurable via SIMILARITY_THRESHOLD (default 0.7)
  • Port: 26350 (NOT the Qdrant default of 6333)
  • API Key: Required -- stored in ~/.ai-memory/docker/.env as QDRANT_API_KEY
  • Decay Scoring: Applied to results via existing search path

Notes

  • GitHub repo is auto-detected from project configuration
  • Results sorted by relevance score (highest first)
  • All filters are optional except the search query
  • Use exact field names from the schema above -- source NOT namespace, type NOT doc_type
  • The source="github" filter is always applied to restrict results to GitHub content
  • The group_id filter is always applied for mandatory tenant isolation (prevents cross-repo leakage)

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