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 skills/chacosoldier/compabob/index-memorynpx skills add chacosoldier/compabob --skill index-memorygit clone --depth 1 https://github.com/chacosoldier/compabobWrote 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/chacosoldier/compabob/index-memory)<a href="https://agentmods.dev/skills/chacosoldier/compabob/index-memory"><img src="https://agentmods.dev/badge/skills/chacosoldier/compabob/index-memory.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 | $0.00043 | $0.00243 |
| Opus 5 | $0.00022 | $0.00121 |
| Sonnet 5 | $0.00009 | $0.00049 |
| Haiku 4.5 | $0.00004 | $0.00024 |
Grade A, and why
index-memory 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 5d 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.
What it actually says
Index Memory
Builds the local search index that the memory-search module uses. Run it after a burst of note-taking, or on a schedule.
Steps
- Run the indexer:
python3 modules/memory-search/index.py - Report back: how many chunks were indexed, and which backend it used. Semantic means search-by-meaning (Ollama with an embedding model is running). Keyword means FTS5 ranked search, the zero-setup default.
- If it used the keyword backend and the user wants search-by-meaning, point
them to
docs/how-to-improve-memory.mdfor the one-time Ollama setup.
Once the index exists, the second-brain agent queries it automatically when
retrieving notes. To keep it current, re-run this skill, or schedule it (see
modules/memory-search/README.md).
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.
- 5d ago First seen · 24 lines · 43 tokens per session scan A 101bc7b189b8
index-memory is a skill published in the GitHub repository chacosoldier/compabob (32 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 243 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
migrate-memory
Migrate legacy NanoClaw and Claude-native memory into the shared memory tree and provider-neutral standing instructions. Run after an update reports the shared-memory breaking change, or when a group still has .seed.md, legacy CLAUDE.md/CLAUDE.local.md, Claude auto-memory, or an unindexed imported-agent-memory.md.…
add-karpathy-llm-wiki
Add a persistent wiki knowledge base to a NanoClaw group. Based on Karpathy's LLM Wiki pattern. Triggers on "add wiki", "wiki", "knowledge base", "llm wiki", "karpathy wiki".
add-mnemon
Add persistent graph-based memory via mnemon. Agents recall past context before responding and remember insights after each turn.
data-sync
Sync and archive data from messaging platforms (WhatsApp, Discord, Slack, Twitter/X, Google) into Moltis memory as daily digest summaries. Orchestrates crawl tools and writes structured markdown to the memory system.
memory-management
Guide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…