talk-maleix-collective-intelligence

Provides detailed answers, conceptual explanations, workflow guidance, and framework-based analysis about Edouard Maleix's talk "How AI-First Dev Teams Build Collective Intelligence — One Attributed Mistake at a Time." Use when the user asks about giving coding agents their own identity and signed commits, the diary/entry/pack/render workflow, turning agent mistakes into reusable team knowledge, evaluating knowledge packs for fidelity and usefulness, voluntary task picking by autonomous agents, the MoltNet open-source project, compound engineering, or applying his approach to make agent lessons compound across a team instead of evaporating into chat history.

Quality

75%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./Plugins/aidevcon/skills/talk-maleix-collective-intelligence/SKILL.md

Quality

Content

63%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, actionable reference skill with a clear grounded lookup workflow and safety rules, weakened by significant redundancy between its two grounding sections and by referenced companion files that are not bundled. The workflow and actionability are solid; conciseness and progressive disclosure are the weak points.

Suggestions

Deduplicate 'Grounding rules' and 'Standard lookup procedure' — they overlap ~80% (read outline → read transcript → cite line ranges → say if absent → flag added content). Merge into one canonical procedure and have each use-case section reference it to recover token budget.

Ship the referenced companion files (outline.md, transcript.md, quote.md) under ./references/ (or state explicitly that they are externally supplied), so the one-level-deep references the body instructs Claude to read actually resolve.

Fix the repeated grammar error 'a safe excerpts' (appears ~5 times) to 'safe excerpts' or 'a safe excerpt' during the conciseness pass.

Dimension	Reasoning	Score
Conciseness	The 'Grounding rules' (6 items) and 'Standard lookup procedure' (5 steps) overlap roughly 80% (read outline → read transcript → cite line ranges → say if absent → flag added content), which is more than minor over-explanation; the repeated 'a safe excerpts' grammar error across ~5 locations also signals untrimmed text, keeping it at anchor 3 rather than 4.	3 / 5
Actionability	Guidance is concrete and executable for an instruction-only skill (specific phrases to use, cite-by-line-range, flag with '[not from talk — added as a starting placeholder]', verdict labels covered/partial/missing), but it stops short of anchor 5 because no full concrete output example (e.g., a sample rendered diary entry or pack) is provided.	4 / 5
Workflow Clarity	Multi-step processes are clearly sequenced with explicit grounding validation checkpoints (missing-file handling, 'say if not in transcript', 'ask before scoring' for undescribed dimensions) and a 3-dimension audit checklist, but there is no true validate→fix→retry recovery loop, so it sits at anchor 4 rather than 5.	4 / 5
Progressive Disclosure	SKILL.md is well organized into clear sections and signals one-level-deep companion files (outline.md, transcript.md, quote.md), but none of those referenced files are actually present in the bundle (no references/ directory), so the disclosure chain cannot be navigated, pulling it down from anchor 4.	3 / 5
	Total	14 / 20 Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, well-targeted description that clearly states what the skill does and gives an explicit, extensive 'Use when' trigger list tied to a single distinctive talk. The only soft spot is that the named actions are abstract service categories rather than concrete operations.

Dimension	Reasoning	Score
Specificity	Lists several distinct service types ('detailed answers, conceptual explanations, workflow guidance, and framework-based analysis') for a clearly named domain, but the actions are abstract service categories rather than concrete operations, so it stops short of anchor 5.	4 / 5
Completeness	It explicitly answers both 'what' (provides answers/explanations/guidance/analysis about the talk) and 'when' (a concrete 'Use when...' clause with multiple trigger phrases), matching the anchor 5 example directly.	5 / 5
Trigger Term Quality	The 'Use when the user asks about...' clause enumerates many natural trigger phrases (signed commits, diary/entry/pack/render workflow, voluntary task picking, compound engineering), giving good coverage, but the terms lean talk-specific jargon with few synonyms, missing anchor 5's comprehensive-synonym bar.	4 / 5
Distinctiveness Conflict Risk	It is scoped to a single named talk by a specific speaker with highly distinctive triggers (MoltNet, attributed mistakes, diary/pack/render), giving it a clear niche with minimal conflict risk against other skills.	5 / 5
	Total	18 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning

	Total	15 / 16 Passed

Repository: jscraik/Agent-Skills
Path: Plugins/aidevcon/skills/talk-maleix-collective-intelligence/SKILL.md
Commit: a3808a9

Reviewed: ~3 hours ago

Table of Contents

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