continual-learning

Orchestrate continual learning by delegating transcript mining and AGENTS.md updates to `agents-memory-updater`.

Quality

69%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./continual-learning/skills/continual-learning/SKILL.md

Quality

Content

92%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.

This is a tight, well-structured orchestration skill that earns top marks for conciseness, workflow clarity, and progressive disclosure, with only a minor actionability gap around what to pass to the delegated subagent. It exemplifies the simple-skill pattern done right.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence — a one-line purpose, a tight trigger, a two-step workflow, and a short guardrail list with no padding or explanation of concepts Claude already knows.	5 / 5
Actionability	The workflow gives concrete executable guidance ('Call `agents-memory-updater`', 'Return the updater result') and guardrails forbid bypassing the subagent, but it does not specify what context or arguments to pass to the subagent, leaving a minor gap.	4 / 5
Workflow Clarity	The two-step sequence (call subagent, return result) is unambiguous and the guardrails reinforce the orchestration-only boundary; this delegation is non-destructive and non-batch, so no validation checkpoint is required, qualifying for the simple-skill exception.	5 / 5
Progressive Disclosure	At under 50 lines with no external references needed, the body is well-organized into clearly labeled Trigger, Workflow, and Guardrails sections, meeting the simple-skill bar for progressive disclosure.	5 / 5
	Total	19 / 20 Passed

Description

46%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 is specific and names a concrete subagent dependency, giving it a clear niche, but it omits any explicit 'Use when...' trigger guidance and relies on jargon over natural user phrasing. Completeness is capped at 3 because the 'when' is missing from the description itself.

Suggestions

Add an explicit 'Use when...' clause naming natural user phrasing (e.g. 'Use when the user asks to mine prior chats, update AGENTS.md, or run the continual-learning loop').

Swap internal jargon for terms users actually say, adding synonyms like 'review past conversations' alongside 'transcript mining'.

Briefly state the concrete outcome so the 'what' reads as a capability rather than an orchestration verb alone.

Dimension	Reasoning	Score
Specificity	Names the continual-learning domain and a few concrete actions ('delegating transcript mining and AGENTS.md updates' to a named subagent), but the verbs 'orchestrate' and 'delegating' stay high-level rather than enumerating comprehensive capabilities.	3 / 5
Completeness	It clearly answers 'what' (orchestrate continual learning via delegation) but provides no 'when' guidance in the description; per the rubric a missing 'Use when...' clause caps completeness at 3.	3 / 5
Trigger Term Quality	It surfaces domain terms like 'continual learning', 'transcript mining', and 'AGENTS.md', but these read as internal jargon and it omits the natural trigger phrases a user would actually say, with no 'Use when...' phrasing.	2 / 5
Distinctiveness Conflict Risk	The named dependency on `agents-memory-updater` and the narrow continual-learning focus carve a clear niche, with only minor overlap risk against general memory/AGENTS.md maintenance skills.	4 / 5
	Total	12 / 20 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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: cursor/plugins
Path: continual-learning/skills/continual-learning/SKILL.md
Commit: 5bf2b15

Reviewed: 15 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.