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/jansenanalytics/claudex/raggit clone --depth 1 https://github.com/JansenAnalytics/claudexWhat 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 | $0.00014 | $0.00355 |
| Opus 5 | $0.00007 | $0.00178 |
| Sonnet 5 | $0.00003 | $0.00071 |
| Haiku 4.5 | $0.00001 | $0.00036 |
Grade A, and why
rag scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Semantic search across Claudex's memory store, session transcripts, and cross-agent context. Requires OPENAI_API_KEY (used for embeddings).
- Run
node --experimental-sqlite ~/.claude-agent/scripts/memory-search.cjs --search "$ARGUMENTS" --limit 10. If it errors on a missing OPENAI_API_KEY, say so plainly — that's the fix, not a bug. - If zero results, retry once without any
--source/--agentfilters. Still nothing → suggestnode --experimental-sqlite ~/.claude-agent/scripts/memory-search.cjs --index --incrementalto refresh the index, then re-run. - Present the top hits, Telegram-friendly, one bullet each:
[memory|session|cross-agent]source tag + score (e.g.0.82)- 1-2 line snippet of the matched content
- file/line ref in
code(e.g.memory/2026-05-12.md:14)
- End with: "Drill into a hit?" — offer to open any one and read it in full.
Filter options to mention if useful (don't run unprompted): --source memory|session|cross-agent to scope, --agent kite|argus for a specific sister agent's context.
Output: bullets only, no tables, no preamble. Lead with a one-line verdict (✅ N hits / ⚠️ weak matches / ❌ nothing).
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.
- yesterday First seen · 20 lines · 14 tokens per session scan A 9fa4f2688c85
rag is a command published in the GitHub repository JansenAnalytics/claudex (5 stars, last pushed 2mo ago), licensed MIT. It adds 14 tokens to every session and 355 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
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.