CtrlK
BlogDocsLog inGet started
Tessl Logo

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

View guide

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 guiding Claude through answering questions about a specific talk. Its greatest strengths are the highly actionable, clearly sequenced workflows for different use cases and the rigorous grounding rules that prevent hallucination (verbatim quoting, explicit acknowledgment of gaps, handling transcription artefacts). The main weaknesses are some repetition across the five workflow sections and the inability to verify the referenced bundle files exist.

Suggestions

Consolidate the repeated 'read outline.md → read transcript.md → quote verbatim → cite lines' pattern into a single shared procedure referenced by each use case, reducing redundancy across the five sections.

Ensure bundle files (outline.md, transcript.md, quotes.md) are included so the progressive disclosure structure can be fully validated and the skill is self-contained.

DimensionReasoningScore

Conciseness

The content is reasonably well-structured but includes some verbose explanatory framing (e.g., the opening paragraph explaining who Debois is and what the talk argues). The grounding rules and workflow sections are mostly efficient, though some instructions are somewhat repetitive across the different use-case sections (e.g., the 'read outline.md then transcript.md then quote verbatim' pattern is repeated four times with minor variations).

2 / 3

Actionability

The skill provides highly concrete, step-by-step guidance for each use case (factual Q&A, applying frameworks, auditing, teaching, proactive surfacing). Instructions are specific about what to do (read outline.md first, quote verbatim, cite line numbers, use the three pillars × three org levels matrix, give covered/partial/missing verdicts). The grounding rules are precise and actionable constraints.

3 / 3

Workflow Clarity

Each workflow is clearly sequenced with numbered steps and explicit validation checkpoints (e.g., 'If the answer genuinely isn't in the transcript, say so explicitly', 'If the framework genuinely doesn't fit, say so', 'If the user hasn't described their state for a dimension, ask before scoring'). The audit workflow includes a clear feedback loop of asking before scoring and a summarization step using the barrel metaphor.

3 / 3

Progressive Disclosure

The skill references external files (outline.md, transcript.md, quotes.md) with clear navigation instructions, which is good progressive disclosure. However, no bundle files were provided, so we cannot verify these references exist. The SKILL.md itself is somewhat long with five detailed use-case sections that could potentially be split, but the content is organized with clear headers. The instruction to check quotes.md first before transcript.md is a nice layered approach.

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 Patrick Debois — and enumerates the key concepts and trigger terms comprehensively. The explicit 'Use when' clause at the start and the rich set of specific terminology make it easy for Claude to select this skill precisely when needed. The only minor note is that it's a single long sentence, but the content quality is excellent.

DimensionReasoningScore

Specificity

The description lists multiple specific concrete concepts: three pillars (Enablement, Platform, Governance), Context Development Lifecycle, agent KPIs like turns-per-task, harnesses and shared context libraries, the barrel mental model, continuous learning as the next CI/CD, and specific roles like AI product engineers and VPs/team leads.

3 / 3

Completeness

The description explicitly opens with 'Use when the user asks about...' providing a clear trigger clause, and the extensive list of topics effectively communicates what the skill covers. Both 'what' (knowledge about this specific talk and its concepts) and 'when' (when users ask about these topics) are clearly addressed.

3 / 3

Trigger Term Quality

Excellent coverage of natural terms a user would say: 'Patrick Debois', 'agent enablement', 'three pillars', 'turns-per-task', 'scaling AI coding agents', 'Context Development Lifecycle', 'org chart', 'platform teams', 'harnesses', 'shared context libraries'. These are highly specific and match how someone familiar with this talk would phrase questions.

3 / 3

Distinctiveness Conflict Risk

This is extremely distinctive — it's scoped to a specific talk by a named speaker with highly specific concepts like 'barrel mental model', 'turns-per-task', and 'Context Development Lifecycle applied to org charts'. It is 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

Table of Contents