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 ai-analyst-lab/ai-analyst-plugin --skill knowledge-bootstrapgit clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst-pluginWrote 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/ai-analyst-lab/ai-analyst-plugin/knowledge-bootstrap)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/knowledge-bootstrap"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/knowledge-bootstrap/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst-plugin/knowledge-bootstrap"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst-plugin/knowledge-bootstrap.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00078 | $0.03141 |
| Opus 5.5 | $0.00031 | $0.01256 |
| Sonnet 5.5 | $0.00016 | $0.00628 |
| Haiku 4.5 | $0.00008 | $0.00314 |
Grade A, and why
knowledge-bootstrap 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 1mo 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The full tree this skill creates is defined in docs/KNOWLEDGE.md (the .knowledge contract). Create exactly that layout.
Skill: Knowledge Bootstrap
Purpose
Initialize all 7 knowledge subsystems for a new session. Loads setup state, dataset, user profile, integrations, org context, corrections, learnings, query archaeology, and analysis archive into working memory.
When to Use
- At the start of any session
- After
/connect-dataor/switch-dataset - When the system detects missing or stale knowledge files
Instructions
Load each subsystem in order. Every file read MUST gracefully degrade: if the file does not exist, skip silently and note "not yet populated" in the summary. Never block the session on a missing subsystem.
Step 1: Setup State
Read .knowledge/setup-state.yaml.
- Parse
setup_completeand count phases withstatus: "complete". - If
setup_complete: false, note the incomplete phases; offer/connect-datafor data connections and a rerun of this skill for the memory tree. - If missing: Note "Setup: not initialized" and continue (this file is optional; connect-data and this skill do the actual setup).
Step 2: Active Dataset
Read .knowledge/active.yaml.
- If
active_datasetis null or missing, note "No active dataset" and continue. - Resolve the context source first. Read
.knowledge/context-source.yaml. If it exists and sayssource: git, sync the team's communal context repo: clone therepoit names into the cache dir (itscachevalue, default.knowledge/.context-cache) if not already cloned, otherwise fetch + checkout + pull theref(defaultmain); thenctx_diris{cache}/{dataset_path}(defaultdatasets/{active}) and the source is "git". If the file is missing or sayssource: local,ctx_diris the in-folder.knowledge/datasets/{active}/and the source is "local". Load the dataset knowledge (semantic/, metrics/, schema.md, quirks.md) fromctx_direither way - the same loader, the source just differs. Report the source ("context: local" or "context: team repo @ {ref}") in the readiness summary. - Load from
ctx_dir:
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.
- 1mo ago First seen · 254 lines · 78 tokens per session scan A f917e6289aea
knowledge-bootstrap is a skill published in the GitHub repository ai-analyst-lab/ai-analyst-plugin (33 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 3,141 once invoked, about $0.0003 per session on Opus 5.5. 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.
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