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ainativedev/aidevcon-2026-ldn

AI Native DevCon 2026 London — all conference sessions as interactive skills

71

Quality

89%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

Overview
Quality
Evals
Security
Files

Quality

Content

77%

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

This is a well-crafted skill for grounding Claude's responses in a specific talk transcript. Its greatest strengths are the highly actionable, clearly sequenced workflows for each use case and the careful handling of edge cases (speech-to-text artifacts, speaker attribution, out-of-scope questions). The main weakness is moderate repetition across the five subsections — the core 'consult outline → read transcript → quote verbatim' pattern could be factored out into a shared preamble to save tokens.

Suggestions

Factor out the repeated 'read outline.md → read transcript.md → quote verbatim → cite line numbers' pattern into a single shared procedure referenced by each subsection, reducing token cost by ~30%.

Consider splitting the five 'How to help' subsections into a separate reference file (e.g., WORKFLOWS.md) with the SKILL.md providing a concise overview and links, improving progressive disclosure.

DimensionReasoningScore

Conciseness

The skill is moderately efficient — the grounding rules and task-specific sections are well-structured, but there's noticeable repetition across sections (e.g., the 'read outline.md → read transcript.md → quote verbatim' pattern is restated nearly identically in every subsection). The opening summary paragraph is somewhat long but does contain useful context. Some tightening is possible without losing clarity.

2 / 3

Actionability

Each section provides concrete, step-by-step instructions for how to handle different user request types. The guidance is specific: which files to consult, in what order, how to quote, how to handle gaps, how to mark non-talk content. The speaker attribution rules and speech-to-text artifact handling are particularly actionable and precise.

3 / 3

Workflow Clarity

Each workflow (factual Q&A, applying the approach, teaching concepts, drafting artifacts, proactive surfacing) is clearly sequenced with numbered steps. Validation checkpoints are present — e.g., checking outline.md before transcript.md, verifying claims exist before answering, flagging when content goes beyond the talk. The feedback loops for edge cases (claim not in transcript, approach doesn't fit user's situation) are explicit.

3 / 3

Progressive Disclosure

The skill references supporting files (outline.md, transcript.md, quotes.md) appropriately and with clear navigation signals. However, no bundle files were provided, so we can't verify the references resolve correctly. The content itself is somewhat monolithic — the five subsections under 'How to help with this talk' could potentially be split into separate reference files given their length and repetitive structure, though for a skill of this size it's borderline acceptable.

2 / 3

Total

10

/

12

Passed

Description

100%

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

This is a strong, well-crafted skill description that clearly identifies its niche (a specific conference talk by a named individual) and provides extensive trigger terms covering the talk's key topics. The explicit 'Use when' opening and the breadth of specific concepts mentioned make it highly effective for skill selection. The only minor concern is that it's quite long, but the density of specific terms justifies the length.

DimensionReasoningScore

Specificity

Lists multiple specific concrete elements: shared-brain setup, OpenClaw + Obsidian + Telegram + GitHub vault stack, per-client vault sections (brand DNA, AD preferences, delivery dates), promote-to-vault discipline, cron-based research agents, chief-of-staff agent concept, recording tools (Granola, OB open-source recorder), and knowledge-management philosophy.

3 / 3

Completeness

The description opens with an explicit 'Use when' clause that clearly answers both what (knowledge about Robert Overweg's talk covering Leapfrog A.I.'s shared-brain setup, vault architecture, agent concepts, recording practices) and when (when the user asks about the talk, its specific topics, or applying the approach to their own work).

3 / 3

Trigger Term Quality

Includes highly specific natural trigger terms a user would say: 'Robert Overweg', 'One Brain No Filtering', 'Leapfrog A.I.', 'OpenClaw', 'Obsidian', 'Telegram', 'GitHub vault', 'brand DNA', 'cron-based research agents', 'chief-of-staff agent', 'Granola', 'knowledge-management', 'agent-orchestration'. These are precise terms someone asking about this specific talk would use.

3 / 3

Distinctiveness Conflict Risk

Extremely distinctive — it's scoped to a specific person's specific talk with named tools and concepts. It would be nearly impossible to accidentally trigger this skill for unrelated queries, and it clearly occupies a unique niche among any set of skills.

3 / 3

Total

12

/

12

Passed

Validation

81%

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

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

Total

9

/

11

Passed

Reviewed

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