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save-learning

Saves user instructions as persistent learnings for future sessions. Use when the user says 'remember this', 'always do X', 'from now on', 'never do Y', or gives any instruction they want persisted across sessions. Proactively suggest when the user states a preference, convention, or rule they clearly want followed in the future.

76

Quality

93%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

87%Weight 40%Scale 1-3

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

A compact, highly actionable skill body with executable commands and concrete worked examples. The only gap is the absence of an explicit verification/feedback step after persisting a learning, which is worth adding given the mutating nature of the operation.

Suggestions

Add a post-save verification step, e.g. running `caliber learn list` or echoing back the saved learning, so Claude can confirm the write actually persisted (closes the workflow_clarity feedback-loop gap for a mutating operation).

Clarify error handling when `caliber learn add` fails (e.g., the learnings file is missing or the command errors) so Claude knows whether to retry, abort, or inform the user.

Make the confirmation gate's failure path explicit — state what to do if the user declines (e.g., 'If declined, do nothing and acknowledge') so the workflow is fully symmetric.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — a tight numbered process, type prefixes, and worked examples with no explanatory padding of concepts Claude already knows, matching anchor 3.

3 / 3

Actionability

Provides fully executable commands (caliber learn add, git add CALIBER_LEARNINGS.md) and concrete copy-paste-ready examples, matching anchor 3 rather than pseudocode or vague description.

3 / 3

Workflow Clarity

Steps are clearly sequenced with a confirmation checkpoint before the mutating add, but a persist/write operation lacks an explicit post-action verification or feedback loop, so it sits at anchor 2 rather than 3.

2 / 3

Progressive Disclosure

No bundle files exist and none are referenced; for a simple skill the well-organized Instructions / Examples / When NOT to trigger sections are sufficient to reach anchor 3 under the simple-skills guideline.

3 / 3

Total

11

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12

Passed

Description

100%Weight 40%Scale 1-3

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 well-crafted description that concisely states the skill's purpose and provides explicit, natural trigger terms covering both proactive and reactive use cases. It cleanly answers what and when with no over-claims or fluff.

DimensionReasoningScore

Specificity

Names the concrete action ('Saves user instructions as persistent learnings for future sessions') plus proactive suggestion behavior, going beyond merely naming a domain like anchor 2.

3 / 3

Completeness

Explicitly states what the skill does ('Saves user instructions as persistent learnings...') and when to use it via the 'Use when the user says...' clause, satisfying both halves for anchor 3.

3 / 3

Trigger Term Quality

Embeds natural phrasings users actually say — 'remember this', 'always do X', 'from now on', 'never do Y' — matching the strong coverage expected at anchor 3.

3 / 3

Distinctiveness Conflict Risk

The persist-instructions-across-sessions niche with distinctive trigger phrases is unlikely to overlap with other skills, fitting anchor 3's clear-niche bar.

3 / 3

Total

12

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
caliber-ai-org/ai-setup
Reviewed

Table of Contents

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