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/microsoft/cat-agent-skills/institutional-knowledgenpx skills add microsoft/cat-agent-skills --skill institutional-knowledgegit clone --depth 1 https://github.com/microsoft/cat-agent-skillsWrote 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/microsoft/cat-agent-skills/institutional-knowledge)<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/institutional-knowledge"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/institutional-knowledge.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 | $0.00143 | $0.06043 |
| Opus 5 | $0.00072 | $0.03021 |
| Sonnet 5 | $0.00029 | $0.01209 |
| Haiku 4.5 | $0.00014 | $0.00604 |
Grade A, and why
institutional-knowledge 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 4d 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 — 528 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/institutional-knowledge — Executive Knowledge Preservation
Intent. Build a comprehensive, structured knowledge archive of a senior leader's tenure by mining their Microsoft 365 signals (emails, Teams chats, meetings, OneDrive/SharePoint contributions), distilling decisions/rationale/relationships, and producing a multi-phase document a successor or AI assistant can ground on. Designed for long-tenure senior leaders (3+ years) whose departure would otherwise lose significant decision history and tribal knowledge.
This skill is resumable. Each invocation reads manifest.md and continues where the last session stopped. Plan for a 1-week sprint across multiple sessions.
0. Core operating principles
- The leader curates; you produce. The user (the departing leader, or a delegate working with them) answers clarifying questions and validates. You write everything.
- Decision archaeology is the highest-value output. Bias toward capturing why decisions were made over what projects exist. Successors can read project trackers; they can't recover lost rationale.
- Multi-phase, gated progression. Phase 1 (discovery) → Phase 2 (deep extraction) → Phase 3 (cross-cutting themes) → Phase 4 (gap questionnaire) → Phase 5 (final assembly). Confirm with the user before advancing phases.
- Idempotent ingest. Every signal is keyed by
(source_id, item_id)or(source_id, date). Re-running merges, never duplicates. - Capture before polish. Get raw signals down across all phases before refining. If time runs short, raw breadth beats polished narrowness.
- Privacy. The archive is built from private signals and lives on the user's machine inside their M365 trust boundary. HR / compensation / performance / health content is automatically out of scope. The leader alone decides what to share with the org or successor.
1. First-run bootstrap
Default archive path: $env:USERPROFILE\Documents\institutional-knowledge on Windows/PowerShell hosts, ~/Documents/institutional-knowledge elsewhere. Some Cowork/Scout sandboxes expose a different writable root and may not set $env:USERPROFILE — if the default path can't be resolved or written, discover a writable Documents/-equivalent folder from the host and confirm it with the user before scaffolding. Detection: an AGENTS.md containing the marker institutional-knowledge-schema-v1 in its first 200 chars (written during scaffold — see §1.4).
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 528 lines · 143 tokens per session scan A 943b4e851a9c
institutional-knowledge is a skill published in the GitHub repository microsoft/cat-agent-skills (63 stars, last pushed 2d ago), licensed MIT. It adds 143 tokens to every session and 6,043 once invoked, about $0.0007 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.
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