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talk-roberts-ai-native-brownfield

Use when the user asks about Katie Roberts''s talk "Stop Maintaining, Start Evolving: Applying AI-Native Practices to Brownfield Codebases" — including questions about using AI to build large complex systems (her ~350k-line Rust S3 clone experiment), test oracles, flaky tests with AI agents, why 100% test coverage is the wrong goal, human-in-the-loop AI coding, AI-assisted performance engineering, using the type system to enforce invariants, tracing as an AI debugging tool, or applying her approach to brownfield/legacy modernisation work.

Quality

89%

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

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

A well-engineered instruction-only reference skill: a precise retrieval workflow with explicit grounding, attribution, and honesty checkpoints, concrete fallback phrases, and clear one-level-deep file navigation. Minor flaws — the "Two files" supporting list omitting quote.md, some cross-section redundancy, and a small grammatical slip ("a safe excerpts") — keep conciseness and progressive disclosure at 4.

Suggestions

Fix the "Two files accompany this skill" claim to include `quote.md`, or move quote.md into the Supporting files list, so the file inventory is complete and consistent.

Tighten the four "How to help" subsections by stating the shared retrieval workflow once and having each subsection add only its task-specific steps, instead of repeating "Follow the workflow above to retrieve and quote".

Fix the typo "anchoring each step in a safe excerpts" (line 46) and similar small wording slips.

DimensionReasoningScore

Conciseness

The body assumes Claude's competence (no explanation of what transcripts, test oracles, or refactoring are) and every section carries guidance. But the four "How to help" subsections each restate "Follow the workflow above to retrieve and quote" and "safe excerpts" is repeated roughly five times — minor redundancy that could be trimmed, matching anchor 4 rather than anchor 5's "every token earns its place". Not 3 because there is no genuine padding or explanation of known concepts.

4 / 5

Actionability

Fully executable instruction-only guidance: exact steps ("Read `outline.md` to find the relevant section(s)", "Read the corresponding range(s) of `transcript.md`", "Cite line numbers"), exact fallback phrases ("the talk doesn't address this", "Katie Roberts made a related point in her brownfield AI-native talk..."), a defined consult order ("check `quote.md` first"), and concrete heuristics ("one quote is usually enough", "If the connection feels strained, stay quiet"). Matches anchor 5's specific coverage of the common cases; not 4 because no key execution details are missing.

5 / 5

Workflow Clarity

The core workflow is a numbered five-step sequence with explicit validation checkpoints: claim grounding ("If a claim isn't in `transcript.md`, say 'the talk doesn't address this' — do not infer positions from outside knowledge"), attribution verification ("Cross-reference any named addressee with the participants list"), and honest-gap handling (the Strangler Fig disclosure). Each sub-workflow (apply, teach, factual Q&A, proactive) has its own numbered steps. Matches anchor 5; no destructive or batch operations, so no feedback-loop cap applies.

5 / 5

Progressive Disclosure

Good structure with one-level-deep, well-signaled references: the "Supporting files" section describes each file's contents, and navigation between them is specified (outline → transcript ranges; quote.md before full transcript search). However, "Two files accompany this skill" lists only `outline.md` and `transcript.md` while `quote.md` is introduced later as a third accompanying file — a minor organization gap fitting anchor 4 rather than 5. (The referenced files are also not present in the provided bundle to verify.) Not 3 because no content that belongs in a separate file is inlined and all references are clearly signaled.

4 / 5

Total

18

/

20

Passed

Description

86%Weight 40%Scale 1-5

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

A strong trigger-focused description: it names a specific talk and speaker and enumerates the talk's topics as natural, comprehensive trigger phrases with no vague padding. Its main weakness is that the skill's capability (the "what") is only implied by "questions about" rather than explicitly stated, holding completeness and specificity just below the top anchors.

Suggestions

State the capability explicitly alongside the trigger clause (e.g., "Answers questions about the talk and quotes verbatim, line-cited passages from its transcript") so the "what" is as explicit as the "when".

Add trigger terms a user might use before knowing the talk by name (e.g., "MinIO", "object storage", "legacy code modernisation") to widen recall without losing distinctiveness.

DimensionReasoningScore

Specificity

Quotes like "questions about using AI to build large complex systems (her ~350k-line Rust S3 clone experiment), test oracles, flaky tests with AI agents" and "using the type system to enforce invariants" are maximally concrete with no fluff, but the only stated action is handling "questions about" — the enumerated items are topics rather than distinct actions, fitting anchor 4 ("lists several specific actions; minor gaps") more than anchor 5's multiple concrete actions. Not 3 because far more than 1-2 concrete specifics are given.

4 / 5

Completeness

The "when" is explicit and highly detailed ("Use when the user asks about Katie Roberts's talk ... including questions about ..."), but the "what" is only implied by "questions about" — the description never states the skill's capability (e.g., answers, explains, quotes from the talk). Fits anchor 4 (both present, one could be more explicit) rather than 5 (both explicitly answered); not 3 because the when-clause is explicit, not weakly implied.

4 / 5

Trigger Term Quality

Natural phrases a user would actually say: "test oracles", "flaky tests", "why 100% test coverage is the wrong goal", "human-in-the-loop AI coding", "AI-assisted performance engineering", "tracing as an AI debugging tool", plus the synonym pair "brownfield/legacy modernisation" and the full talk title and speaker name. This matches anchor 5's comprehensive coverage including synonyms; not 4 because no natural variations of substance are missing.

5 / 5

Distinctiveness Conflict Risk

Names a specific speaker and talk ("Katie Roberts", "Stop Maintaining, Start Evolving: Applying AI-Native Practices to Brownfield Codebases") with topic triggers unique to that talk — a clear niche with minimal conflict risk, matching anchor 5. Not 4 because no overlap risk with closely related skills exists.

5 / 5

Total

18

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository

jscraik/Agent-Skills

Path

Plugins/aidevcon/skills/talk-roberts-ai-native-brownfield/SKILL.md

Reviewed

Table of Contents

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