Borrowing it
Nothing to install: this file belongs to egregore-labs/egregore. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/egregore-labs/egregore/main/.claude/skills/meeting/SKILL.mdgit clone --depth 1 https://github.com/egregore-labs/egregoreWrote 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/egregore-labs/egregore/meeting)<a href="https://agentmods.dev/skills/egregore-labs/egregore/meeting"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/meeting/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/egregore-labs/egregore/meeting"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/meeting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Agent Snooping · line 294 Skill accesses MCP server configuration files (mcp.json). MCP configs contain server URLs, authentication tokens, and tool definitions — reading them allows the skill to discover and potentially abuse other tool integrations.Fix: Remove all code or instructions that read MCP configuration files (mcp.json). MCP server details should be managed by the agent runtime, not read by individual skills.
- high Agent Snooping · line 300 Skill accesses MCP server configuration files (mcp.json). MCP configs contain server URLs, authentication tokens, and tool definitions — reading them allows the skill to discover and potentially abuse other tool integrations.Fix: Remove all code or instructions that read MCP configuration files (mcp.json). MCP server details should be managed by the agent runtime, not read by individual skills.
- high System Prompt Leakage · line 474 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
- high Anti-Refusal · line 916 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00045 | $0.00840 |
| Opus 5.5 | $0.00018 | $0.00336 |
| Sonnet 5.5 | $0.00009 | $0.00168 |
| Haiku 4.5 | $0.00005 | $0.00084 |
Grade A, and why
meeting 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 24d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meeting
Acquire meeting material, adapt the analysis to the user's intent, preview the result, then persist one approved typed package through Egregore Runtime.
Read references/analysis-contract.md before analysis or package construction.
When to invoke
Analyze a Granola meeting or supplied transcript into an evidence-backed briefing, decisions, findings, patterns, actions, and continuity. Use for /meeting, /meeting sync, /meeting backfill, or requests to process a meeting.
Source
When the user supplies a transcript as pasted text or a file path, analyze it
directly. Take title, date, and attendees from the user or the file; ask only
for missing metadata needed for analysis or writeback. In the Runtime package,
use source type transcript and preserve a supplied stable source ID when
available; otherwise derive the ID as transcript:<sha256> from the acquired
transcript. Use its SHA-256 for content_hash and, when no source revision is
supplied, for revision. This path does not require Granola.
Granola acquisition
The Granola connector is required only to list, search, or fetch meeting material. Use the configured Granola connector to list/search meetings and fetch the selected transcript plus title, date, attendees, source ID, and source revision. Do not copy connector credentials or raw transcripts into canonical memory.
/meeting: list recent candidates and let the user choose./meeting <search>: select an exact result or ask when ambiguous./meeting sync: process selected new candidates with balanced defaults./meeting backfill: re-analyze selected canonical meeting sources; never overwrite newer claims without explicit supersession.
If Granola is unavailable, explain the connection issue and stop. Connector access is source acquisition, not organizational authorization or canonical writeback.
Context and intent
Reuse sufficient EGREGORE_ORG_CONTEXT_V1. Open already-selected canonical
evidence through the Runtime source-open boundary when exact verification is
needed. Do not repeat Observe/search merely because this skill loaded.
What ships with it
1 file 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.
- 24d ago Changed · -957 lines · +4 tokens per session 0e47b4e67d86
- 1mo ago First seen · 1,046 lines · 41 tokens per session scan A a84d971f5531
meeting is a skill published in the GitHub repository egregore-labs/egregore (293 stars, last pushed 9d ago), licensed MIT. It adds 45 tokens to every session and 840 once invoked, about $0.0002 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.
Other skills, from other repositories
trekker
Persistent task memory for AI agents across sessions.
task-sync
Synchronize Trekker with Claude's built-in TodoWrite. Trekker is the source of truth.
sw-project
Keep a project's goal, decisions, work items, artifacts and briefs portable across AI tools and accounts. Use for project coordination, "project brief", "what is this project about".
sibyl
Persistent memory and task coordination for this project. Invoke for any prompt about past work, project state, in-progress tasks, prior decisions, gotchas, or capturing a non-obvious learning. Also covers semantic search across project knowledge and external docs.
alive-bundle
Create, manage, and graduate bundles -- the unit of focused work within a walnut.
knowledge-session-state-and-context
A codebase guide for storing agent sessions, rebuilding their visible state, recovering active work, branching or rewinding history, and shortening context sent to the model.