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feedback-learning

Classify and record explicit corrective feedback without turning skills or instructions into append-only knowledge dumps.

64

Quality

81%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is feedback-learning in microsoft/vscode

SKILL.md
Quality
Evals
Security

Quality

Content

100%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.

The body is an excellent example of an instruction-only skill: dense with non-obvious, repository-specific governance rules, a concrete decision table, a copy-paste-ready artifact template, and a complete lifecycle (record, read selectively, compact, garbage-collect) with validation and checklists. I found no meaningful gaps on any content dimension.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence: no background concepts are explained, and every rule is a real, non-obvious constraint ("Preserve the principle, not the incident chronology", "Never copy the same rule into a skill, instruction, and design document"). I could not identify any padded or over-explanatory passage to justify dropping to 4.

5 / 5

Actionability

The guidance is fully executable for an instruction-only skill: a copy-paste-ready markdown template with concrete fields (Scope, Learning, Evidence, Disposition), a six-row classification table mapping each feedback kind to a concrete destination (regression test, `.github/learnings/<area>.md`, etc.), and exact numeric limits (ten topics, 8 KB, 90 days). Per the scoring notes, absence of code is not penalized when the guidance is this actionable.

5 / 5

Workflow Clarity

The six-step workflow is clearly sequenced with an explicit "Validate" step (confirm destination applies to the affected path, check links, remove superseded guidance), a pre-write compaction gate, and a full review checklist with objective triggering conditions (topic/size limits, 90-day staleness). Validation checkpoints are present, so the destructive/batch cap at 3 does not apply; this matches the anchor with explicit validation steps and checklists for complex processes.

5 / 5

Progressive Disclosure

The skill is a single self-contained SKILL.md with no bundle files and no need for external references; its ~88 lines are appropriately placed inline rather than split. Sections (Goal, Workflow, inbox format, reading rules, compaction) are well-ordered and easy to navigate, with the one external file mention (`.github/instructions/learnings.instructions.md`) clearly signaled as a boundary carve-out rather than buried reference material.

5 / 5

Total

20

/

20

Passed

Description

53%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.

The description states a clear, appropriately narrow purpose with third-person voice and a meaningful anti-pattern constraint, but it omits any explicit trigger guidance and misses the natural phrases a user would say when needing this skill. It is serviceable but below the bar set by the reference good examples, all of which pair a concrete "what" with a "Use when..." clause.

Suggestions

Add an explicit trigger clause to the description, e.g. "Use when the user explicitly corrects an approach, rejects a pattern, or asks the agent to learn from feedback" — this would lift completeness from 3 to 5 and also improve trigger-term quality.

Include natural user phrasings as trigger keywords: "learn from this", "remember this correction", "don't do that again", so the skill surfaces when users give feedback without using the word "feedback".

Optionally name one or two more concrete actions (e.g. where feedback gets routed — tests, design docs, instruction files, a learning inbox) to broaden the action coverage beyond "classify and record".

DimensionReasoningScore

Specificity

"Classify and record explicit corrective feedback" names the domain and exactly two concrete actions; the "without turning skills or instructions into append-only knowledge dumps" clause is a constraint, not a third action. This matches the anchor for domain plus 1-2 concrete actions that is not comprehensive, and falls short of the several (3+) specific actions required for 4.

3 / 5

Completeness

The description clearly answers "what" (classify and record explicit corrective feedback, avoid append-only knowledge dumps) but contains no "Use when..." clause or equivalent explicit trigger guidance, which the judging guidelines cap at 3. This matches the anchor for a clear "what" with "when" missing or only weakly implied via the phrase "explicit corrective feedback".

3 / 5

Trigger Term Quality

"Corrective feedback" and "feedback" are relevant keywords, but common natural phrasings users would actually say — "learn from this", "remember this", "correction", "don't do that again" — are absent from the description. Some relevant keywords with missing variations matches anchor 3; coverage is thinner than anchor 4's "good keyword coverage, a few natural terms missing".

3 / 5

Distinctiveness Conflict Risk

The niche — classifying corrective feedback and preventing append-only knowledge dumps — is mostly distinct, with only minor overlap risk against general memory/notebook-management skills. It lacks the explicit distinct trigger phrases needed for a 5, but is far more specific than the "somewhat specific but could still overlap" anchor at 3.

4 / 5

Total

13

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

posit-dev/positron

Path

.github/skills/feedback-learning/SKILL.md

Reviewed

Table of Contents

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