replay-learnings

Surface past learnings relevant to the current task before starting work. Searches correction history, recalls past mistakes, and applies prior patterns. Use when starting a task, saying "what do I know about", "previous mistakes", "lessons learned", or "remind me about".

1.54x

Quality

73%

Does it follow best practices?

Impact

94%

1.54x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/replay-learnings/SKILL.md

Quality

Content

57%

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

The skill has good structure and a useful output template that makes the expected behavior clear. Its main weakness is that several workflow steps (checking session history, ranking by relevance, computing correction rates) are described abstractly without concrete commands or mechanisms, making them more aspirational than actionable. The grep examples in step 2 are a strong point that should be extended to the other steps.

Suggestions

Provide concrete commands or mechanisms for step 3 (checking session history and computing correction rates) — e.g., how to parse git log or a session log file to derive edit/correction counts.

Clarify step 4 ('surface top learnings ranked by relevance') with a concrete ranking heuristic or algorithm rather than leaving it abstract.

Remove the flavor text opening line ('Like muscle memory...') to improve conciseness — the trigger section already explains when to use the skill.

Dimension	Reasoning	Score
Conciseness	The opening line 'Like muscle memory for your coding sessions' is unnecessary flavor text, and the trigger section partially duplicates the description. However, the workflow and output sections are reasonably tight. Some tightening possible but not egregiously verbose.	2 / 3
Actionability	The grep commands in step 2 are concrete and executable, which is good. However, steps 3-4 ('check session history', 'surface top learnings ranked by relevance') are vague — there's no concrete mechanism for how to check session history or rank learnings. The output example is illustrative but the skill doesn't explain how to generate the correction rate or ranking.	2 / 3
Workflow Clarity	The 5-step workflow is clearly sequenced and includes a fallback (step 5). However, steps 3 and 4 lack specificity on how to accomplish them — there are no concrete commands or validation checkpoints. The workflow is more of a conceptual outline than an executable procedure for several of its steps.	2 / 3
Progressive Disclosure	For a skill of this size and scope (~50 lines, single-purpose), the content is well-organized into clear sections (Trigger, Workflow, Output, Guardrails) without needing external references. No monolithic walls of text or unnecessary nesting.	3 / 3
	Total	9 / 12 Passed

Description

89%

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 solid description that clearly communicates both what the skill does and when to use it, with good trigger terms that users would naturally employ. The main weakness is that the specific actions could be more concrete — 'applies prior patterns' is somewhat vague. Overall, it performs well across most dimensions.

Suggestions

Make the actions more concrete by specifying outputs, e.g., 'Searches correction history and surfaces relevant warnings, anti-patterns, or preferred approaches before work begins.'

Dimension	Reasoning	Score
Specificity	The description names a domain (past learnings/correction history) and some actions ('searches correction history', 'recalls past mistakes', 'applies prior patterns'), but the actions are somewhat abstract and not highly concrete — what does 'applies prior patterns' actually do in practice?	2 / 3
Completeness	Clearly answers both what ('Surface past learnings relevant to the current task, searches correction history, recalls past mistakes, applies prior patterns') and when ('Use when starting a task, saying "what do I know about", "previous mistakes", "lessons learned", or "remind me about"') with explicit trigger guidance.	3 / 3
Trigger Term Quality	Good coverage of natural trigger terms: 'what do I know about', 'previous mistakes', 'lessons learned', 'remind me about', and 'starting a task' are all phrases users would naturally say when wanting to recall prior learnings.	3 / 3
Distinctiveness Conflict Risk	This skill has a clear niche — surfacing past learnings and correction history — with distinct trigger terms that are unlikely to conflict with other skills. The focus on memory recall and past mistakes is quite specific.	3 / 3
	Total	11 / 12 Passed

Validation

100%

Warnings & errors only

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

Validation — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: rohitg00/pro-workflow
Commit: 5c313e2

Reviewed: 14 days ago

Table of Contents

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