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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?

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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 knowledge-grounding skill that provides clear, actionable workflows for answering questions about a specific talk. Its strongest aspects are the explicit grounding rules (never fabricate quotes, cite line numbers, flag non-talk content) and the well-sequenced lookup procedure with validation steps. The main weaknesses are moderate verbosity — some instructions are repeated across sections — and the inability to verify the referenced bundle files.

Suggestions

Consolidate the repeated 'Note for all use-case sections below' into the Standard lookup procedure section itself, and remove per-section reminders to reduce token overhead.

Consider extracting the detailed use-case sections into a separate reference file (e.g., USE_CASES.md) and keeping SKILL.md as a concise overview with the grounding rules and standard procedure.

DimensionReasoningScore

Conciseness

The skill is reasonably well-structured but contains some redundancy — the 'Standard lookup procedure' is restated conceptually in the intro paragraph and then again in each use-case section's preamble. The note about following the standard procedure automatically is repeated. Some sections could be tightened, but overall it avoids explaining things Claude already knows.

2 / 3

Actionability

Each use-case section provides concrete, step-by-step instructions with clear decision points (e.g., when to quote verbatim, when to say 'the talk doesn't address this,' when to flag added content). The grounding rules are specific and executable — they tell Claude exactly what to do with artifacts, attribution, and speech-to-text errors.

3 / 3

Workflow Clarity

The skill defines a clear shared lookup procedure (read outline → read transcript section → ground in quotes → flag gaps) and each use-case section layers additional specific steps on top. Validation checkpoints are present: check outline first, verify claims against transcript, flag anything not from the talk, ask the user before filling gaps. The fallback for missing bundle files is explicit.

3 / 3

Progressive Disclosure

The skill references companion files (outline.md, transcript.md, quotes.md) with clear descriptions of their contents and purpose, which is good structure. However, no bundle files were provided, so we can't verify the references resolve. The SKILL.md itself is fairly long and monolithic — the multiple use-case sections could potentially be split out — but the content is organized with clear headers and the length is justified by the number of distinct use cases.

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 an excellent skill description that clearly defines its scope around a specific talk, lists concrete capabilities, and provides an extensive 'Use when' clause with numerous specific trigger terms. The description is well-structured, uses third person voice correctly, and its narrow focus on a named talk with unique concepts makes it highly distinctive and unlikely to conflict with other skills.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'detailed answers, conceptual explanations, workflow guidance, and framework-based analysis' about a clearly named talk. The description enumerates specific concepts like diary/entry/pack/render workflow, knowledge packs evaluation, voluntary task picking, and MoltNet.

3 / 3

Completeness

Clearly answers both 'what' (provides detailed answers, conceptual explanations, workflow guidance, and framework-based analysis about the specific talk) and 'when' (explicit 'Use when' clause listing numerous specific trigger scenarios like asking about agent identity, the workflow, knowledge packs, MoltNet, etc.).

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms users would say: 'coding agents', 'signed commits', 'diary/entry/pack/render workflow', 'agent mistakes', 'knowledge packs', 'fidelity and usefulness', 'voluntary task picking', 'MoltNet', 'compound engineering', 'collective intelligence'. These are specific phrases someone familiar with the talk would naturally use.

3 / 3

Distinctiveness Conflict Risk

Extremely distinctive — it's scoped to a single specific talk by a named speaker with highly unique concepts (MoltNet, diary/entry/pack/render workflow, compound engineering). Very unlikely to conflict with other 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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