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 retrieval-augmented Q&A skill with strong actionability and workflow clarity. Each use case provides specific, sequenced instructions with clear validation steps (verbatim quoting requirements, explicit 'say so' when information is missing, marking non-talk additions). The main weaknesses are moderate verbosity across the six use-case sections and the inability to verify the referenced bundle files (outline.md, transcript.md, quotes.md) that the entire skill depends on.

Suggestions

Consider consolidating the prerequisites list (CI/CD, platform, tests, coding standards, transparency) into a single reference point rather than repeating elements across the summary and audit section.

The 'Surface this talk proactively' section could be reduced to a brief trigger-list since the retrieval rules and quoting conventions are already established in the core rules.

DimensionReasoningScore

Conciseness

The skill is reasonably well-structured but includes some redundancy across sections (e.g., the prerequisites list appears in both the summary and the audit section). Some sections like 'Surface this talk proactively' could be tightened. However, it largely avoids explaining concepts Claude already knows and focuses on domain-specific instructions.

2 / 3

Actionability

The skill provides highly concrete, specific guidance for each use case: exact file lookup sequences (outline.md → transcript.md), explicit rules for quoting and attribution, named prerequisites with verbatim examples, artifact specifications with concrete details (dates, numbers, shortlist counts), and clear formatting requirements (marking additions as '[not from talk]'). Every section tells Claude exactly what to do.

3 / 3

Workflow Clarity

Each use case has a clearly sequenced workflow (e.g., 'Find section in outline.md → read transcript.md → answer with verbatim quotes → cite section'). The audit workflow includes explicit per-dimension verdicts and a summarization step. The artifact drafting workflow includes a validation pattern: quote the prescription first, then draft, then mark additions. The core retrieval rules establish a clear decision tree for attribution uncertainty and missing information.

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 moderately long with all use cases inline rather than split into separate files, though for a retrieval-augmented Q&A skill this inline approach is arguably appropriate.

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 identifies its narrow domain (a specific conference talk), lists concrete topics it covers, and provides an extensive 'Use when' clause with highly specific trigger terms. The description is thorough without being padded, and its specificity to named individuals, companies, and metrics makes it virtually impossible to confuse with other skills.

DimensionReasoningScore

Specificity

The description lists multiple specific concrete actions and topics: answering questions about a specific talk, covering Odevo's agentic coding rollout, AI-native transformation playbook, prerequisites (CI/CD, platform, tests, coding standards), specific workshop techniques, context window management, specific metrics (94% adoption, 8-years-to-3-weeks rewrite), and bottleneck shifts.

3 / 3

Completeness

Clearly answers both 'what' (answers questions about Daniel Jones and Tomasz's talk on Odevo's AI-native transformation) and 'when' with an explicit 'Use when...' clause listing numerous specific trigger scenarios.

3 / 3

Trigger Term Quality

Excellent coverage of natural terms users would say: 'Odevo', 'agentic coding', 'AI adoption', 'CI/CD', 'liberating structures', 'TRIZ', 'context window management', 'train-the-trainer', 'AI-native transformation', 'everyone a builder'. These are highly specific terms a user familiar with this talk would naturally use.

3 / 3

Distinctiveness Conflict Risk

Extremely distinctive — it references a specific talk by named speakers, a specific company (Odevo), specific metrics, and specific methodologies. This is unlikely to conflict with any other skill due to its highly niche focus.

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