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 skills add kalinbogatzevski/captain-memo --skill statsgit clone --depth 1 https://github.com/kalinbogatzevski/captain-memoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kalinbogatzevski/captain-memo/stats)<a href="https://agentmods.dev/skills/kalinbogatzevski/captain-memo/stats"><img src="https://agentmods.dev/badge/skills/kalinbogatzevski/captain-memo/stats.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00036 | $0.00623 |
| Opus 5 | $0.00018 | $0.00311 |
| Sonnet 5 | $0.00007 | $0.00125 |
| Haiku 4.5 | $0.00004 | $0.00062 |
Grade A, and why
stats scanned grade A with 1 finding 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 7d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s http://127.0.0.1:39888/stats How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Captain Memo — corpus stats
When invoked, fetch the worker's /stats endpoint and present it readably.
What to do
curl -s http://127.0.0.1:39888/stats
The response includes: total_chunks, by_channel, observations (total/queue_pending/queue_processing), indexing (status/done/total/percent/elapsed_s/errors/last_error), project_id, embedder (model/endpoint), efficiency, and worker (started_at_epoch, uptime_s).
A successful /stats response means the backend worker is ONLINE — lead with that
and its uptime. Format worker.uptime_s compactly: 45s / 12m / 2h 13m / 3d 4h.
If the curl fails / connection refused, the worker is OFFLINE — say so and point
the user at captain-memo doctor (see "On error").
Output format
Captain Memo — corpus statistics
────────────────────────────────
Worker: ● online · up 2h 13m
Project: <project_id>
Indexing: ready (or "indexing 47/275 (17%) ETA=3m 12s")
Total chunks: <total>
By channel:
memory <count>
skill <count>
observation <count>
Observations: <total> · <pending> pending · <processing> processing
Embedder: <model> @ <endpoint>
Efficiency
──────────
Compression: 16.4× — distilled 184,320 tokens of work into 11,240 stored
(94% saved · based on 312/340 observations)
Embedder: 47 calls · ~690 ms avg · 4,100 tok/s (since worker start)
Dedup: 95% of docs skipped re-embed (488/512 unchanged)
The efficiency block reports corpus compression (summed observation
work_tokens vs stored_tokens), embedder throughput, and dedup hit-rate.
If compression shows "— (run 'captain-memo reindex' …)", the corpus has no
work_tokens data yet — reindex to populate it.
If indexing.status === "indexing", show the progress in yellow with rate and ETA. If "ready", show in green with "indexed N/N in M". If "error", show the last_error in red.
On error
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.
- 7d ago First seen · 57 lines · 36 tokens per session scan A 3e0b68938d58
stats is a skill published in the GitHub repository kalinbogatzevski/captain-memo (3 stars, last pushed 4d ago), licensed Apache-2.0. It adds 36 tokens to every session and 623 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
memem-mine
Opt in to memem's event-triggered mining. New sessions are mined automatically via the Stop hook.
knowledge-base
Build and maintain a company knowledge base as a wiki of interlinked markdown notes in the workspace — a private, compounding Wikipedia. Use when the user wants to start or organize a knowledge base / wiki, ingest sources (URLs, documents, pasted notes) into it, ask questions answered from it, or audit (lint) it.…
forget
Delete a Wenlan memory by exact id from Codex. Destructive and confirmation gated. Invoked as /forget .
vault-for-llm
Connect OpenClaw to Vault Agent Memory as a local-first governed project memory layer. Search first, then bounded-read cited source ranges; propose new memories as candidates instead of writing directly into active memory.
skills
Your next session starts cold. No memory of what you built, what broke, what you decided. Every memory you write is a gift to that future session. The richer the memory, the less time re-learning.
memem-welcome
Re-show the full memem welcome screen regardless of whether the user has seen it before. Use when the user wants to see the intro, tutorial, or welcome again.