Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/adilkalam/orca/memory-searchgit clone --depth 1 https://github.com/adilkalam/orcaWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00026 | $0.00878 |
| Opus 5 | $0.00013 | $0.00439 |
| Sonnet 5 | $0.00005 | $0.00176 |
| Haiku 4.5 | $0.00003 | $0.00088 |
Grade A, and why
memory-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/memory-search - Unified Memory Search
Search across all memory systems in one command.
Command: /memory-search $ARGUMENTS
What It Searches (federated)
The unified script federates across every durable memory store, so a "why did we choose X" answer surfaces regardless of which store it lives in:
- Workshop (decisions, notes, gotchas, learnings) -- via the
workshopCLI - code-index.db (code chunks, symbols, functions, classes)
- Cognition harvests (
.orca/cognition/**-- cognition session summaries) - Claude auto-memory (
~/.claude/projects/<slug>/memory/MEMORY.md+ linked files) - CLAUDE.md Learned Rules ledger
- orca-record checkpoints (prompt summaries from
.orca/recording.db) - Research Index (optional, if the project has a research-sync script)
Execution
Step 1: Parse Query
Extract the search query from arguments. If empty, show help.
Step 2: Federated search (primary)
The unified script covers Workshop + code-index.db + cognition + auto-memory + Learned Rules + recording in one call:
python3 ~/.claude/scripts/memory-search-unified.py "$QUERY" --mode all --top-k 10 2>/dev/null \
|| echo "unified search unavailable"
Step 4: Search Research Index (if exists)
If the project has a research-sync script (e.g., .claude/scripts/research-sync.py), also search research chunks:
# Only run if research-sync script exists in the project
if [ -f .claude/scripts/research-sync.py ]; then
python3 .claude/scripts/research-sync.py search "$QUERY" --limit 10 2>/dev/null || true
fi
Step 5: Present Unified Results
Format the output clearly:
Memory Search: "<query>"
=== WORKSHOP (Decisions/Notes) ===
[Results from workshop search, or "No matches found"]
=== CODE (code-index.db) ===
[Results from code-index hsearch, formatted as:]
| Type | Name | File | Score |
|----------|-------------------|-------------------------------|-------|
| function | handleAuth | src/auth/jwt.ts:45 | 0.85 |
| class | AuthService | src/services/auth.ts:12 | 0.72 |
[Or "No matches found" / "Run /project-code sync first"]
=== RESEARCH (if indexed) ===
[Results from research-sync search, formatted as:]
| Type | Title | Section | Score |
|-------------|------------------------------------|--------------------- |-------|
| source_note | Sara Roy: If Israel Were Smart | The WikiLeaks Cable | 0.85 |
| reflection | LLM Reflection V6 | The Apparatus | 0.72 |
[Or skip section if research-sync.py doesn't exist]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 123 lines · 26 tokens per session scan A 12d525ec1010
memory-search is a command published in the GitHub repository adilkalam/orca (2 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 878 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.