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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-structured reference skill for answering questions about a specific conference talk. Its greatest strengths are actionability (clear step-by-step workflows for each use case) and workflow clarity (explicit validation steps and boundary handling). The main weaknesses are moderate repetition across sections (the 'read outline → read transcript → quote verbatim' pattern is restated five times) and the inability to verify the referenced bundle files (outline.md, transcript.md, quotes.md).

Suggestions

Reduce repetition by extracting the common 'read outline.md → read transcript.md → quote verbatim → cite line numbers' pattern into a single 'Standard lookup procedure' section referenced by each use case, rather than restating it in every section.

Consolidate the grounding rules and per-section instructions to eliminate overlap — e.g., rules 1-3 in 'Grounding rules' are repeated almost verbatim in 'Factual Q&A about the talk'.

DimensionReasoningScore

Conciseness

The skill is reasonably efficient for its complexity — it covers multiple use cases (Q&A, audit, teach, apply, proactive surfacing) without excessive padding. However, some sections are repetitive (e.g., 'read outline.md then transcript.md' and 'verbatim quotes' instructions are restated in nearly every section), and the grounding rules overlap significantly with the per-section instructions. Could be tightened by ~30%.

2 / 3

Actionability

Each use case has concrete, step-by-step instructions with specific actions (read outline.md first, quote verbatim, cite line numbers, walk through every dimension in order, give covered/partial/missing verdicts). The audit section even specifies the exact checklists to use. The guidance is specific and directly executable by Claude.

3 / 3

Workflow Clarity

Multi-step processes are clearly sequenced (e.g., 'read outline.md → find section → read transcript.md → answer with quotes → cite sources'). Validation checkpoints are present: 'If the answer isn't in the transcript, say so explicitly,' 'If a dimension doesn't apply, say so,' 'If the user hasn't described their state, ask before scoring.' Error handling and boundary conditions are well-addressed.

3 / 3

Progressive Disclosure

The skill references external files (outline.md, transcript.md, quotes.md) with clear navigation instructions, which is good progressive disclosure design. However, no bundle files were provided, so we cannot verify these references exist. The SKILL.md itself is somewhat long and could benefit from splitting the five use-case sections into separate files, keeping only the grounding rules and a brief overview inline.

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 description that clearly identifies a narrow, distinctive niche — knowledge about a specific conference talk. It opens with an explicit 'Use when' clause, lists comprehensive trigger terms covering the talk's key concepts, and is highly unlikely to conflict with other skills. The only minor concern is its length, but the specificity justifies it.

DimensionReasoningScore

Specificity

The description lists multiple specific concrete concepts: failure modes (overlap, drift, activation, rot, overloading), the agentic equation components, CDLC, skill registries, evals, and specific recommendations (decompose, extend don't edit, version control, automated reviews, registry, agent-agnostic skills).

3 / 3

Completeness

Clearly answers both what (knowledge about James Moss's specific talk and its concepts) and when ('Use when the user asks about...' with an explicit and comprehensive list of trigger scenarios).

3 / 3

Trigger Term Quality

Excellent coverage of natural terms a user would say: the speaker's name 'James Moss', the talk title, 'DevCon 2026', 'Tessl', specific concepts like 'skills sprawl', 'CDLC', 'skill registries', 'agentic equation', and each failure mode and recommendation by name. These are highly specific and natural trigger terms.

3 / 3

Distinctiveness Conflict Risk

Extremely distinctive — it references a specific person, a specific talk title, a specific conference and year, and highly specific concepts like 'CDLC', 'agentic equation', and named failure modes. This is very unlikely to conflict with any other skill.

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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