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 jscraik/Agent-Skills --skill talk-maleix-collective-intelligencegit clone --depth 1 https://github.com/jscraik/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/jscraik/agent-skills/talk-maleix-collective-intelligence)<a href="https://agentmods.dev/skills/jscraik/agent-skills/talk-maleix-collective-intelligence"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/talk-maleix-collective-intelligence/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/jscraik/agent-skills/talk-maleix-collective-intelligence"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/talk-maleix-collective-intelligence.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00131 | $0.02030 |
| Opus 5.5 | $0.00052 | $0.00812 |
| Sonnet 5.5 | $0.00026 | $0.00406 |
| Haiku 4.5 | $0.00013 | $0.00203 |
Grade A, and why
talk-maleix-collective-intelligence 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
How AI-First Dev Teams Build Collective Intelligence — Edouard Maleix
Edouard Maleix argues that coding agents currently produce lessons every session but the team never learns from them — corrections evaporate into closed chat windows. He proposes a three-act workflow: (1) give agents their own identity and signed commits so work is attributable, capturing rationale in a "diary" of entries; (2) curate entries into thematic "packs" rendered into agent-readable skills that preserve attribution; (3) run controlled evals for fidelity and usefulness, eventually moving toward voluntary task-picking by specialized autonomous agents. The thesis: mistakes should compound into collective intelligence, not disappear into chat history.
Expected bundle files
This skill references two companion files that should be present in the same bundle:
outline.md— A structured map of the talk, with sections keyed to approximate transcript line ranges and two lookup tables: "Named frameworks / concepts" (e.g. Identity & Diary; Pack, Curation & Render; Evals & Autonomy) and a "Terminology glossary" (e.g. diary, entry, pack, render, fidelity eval, usefulness eval, voluntary task picking, compound engineering).transcript.md— The raw speech-to-text transcript of the talk, line-numbered. The bulk is Edouard speaking; a Q&A section at the end interleaves unnamed audience questions with his answers.
If either file is missing, tell the user you cannot ground your answer and ask them to provide the relevant passage directly.
Grounding rules — MUST follow when answering
- Before answering any specific question, read
outline.mdto locate the relevant section, then read that section oftranscript.md. - When attributing words, quote short, non-sensitive excerpts from
transcript.md. Never put quotation marks around paraphrased content. - If a claim isn't in
transcript.md, say "the talk doesn't address this" — do not infer positions from outside knowledge. - Cite by transcript line range whenever possible.
- Speaker attribution is unreliable at the sentence level for this transcript — it has no per-speaker labels and includes obvious speech-to-text artifacts (e.g. "Adrian" / "adrian" almost certainly meant "AI"; "globally" likely meant "Claude"; "Tagli" likely "tiny"; "MoltNet" appears once in the abstract but may be transcribed differently in the body). The bulk of the transcript is Edouard speaking; the Q&A at the end interleaves audience questions with his answers. When quoting, preserve the artifacts verbatim — do not silently correct them — but you may note "(likely 'AI')" inline when the meaning is unambiguous from context.
- Cross-reference any named addressee with the speaker bio /
outline.mdbefore attributing. Audience questioners are unnamed; refer to them as "an audience member" or "a questioner."
What ships with it
4 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.
- 1mo ago First seen · 105 lines · 131 tokens per session scan A dd8388141802
talk-maleix-collective-intelligence is a skill published in the GitHub repository jscraik/Agent-Skills (9 stars, last pushed yesterday), licensed Apache-2.0. It adds 131 tokens to every session and 2,030 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
agent-challenges
Agent skill for challenges - invoke with $agent-challenges.
moai-workflow-jit-docs
Enhanced Just-In-Time document loading system that discovers, loads, and caches relevant documentation based on user intent and project context. Use when users need specific documentation on demand.
continuous-learning
Pattern extraction, confidence-scored evaluation, skill creation, organization, versioning, and cross-project export pipeline.
note
Generate study notes from a lecture transcript and slides. Runs transcript + slide download in parallel, then writes a Markdown note with timeline outline.
trans
Transcribe a single Tongji Look lecture video to SRT + TXT, optionally download slide snapshots in parallel.
list
Discover and select courses from Tongji Look (look.tongji.edu.cn). Lists recent or all courses, filters by keyword, and saves the chosen course for use with /trans, /note, and other commands. Prerequisite for all lecture workflows.