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reasoningbank-learning

Use agentic-flow's ReasoningBank to learn from past work - search similar episodes before a task, record reward, success and critique after it, and read trends. Use when the user wants agents to remember what worked, or asks about ReasoningBank, pattern store/search, or self-learning.

Quality

89%

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SKILL.md
Quality
Evals
Security

Quality

Content

86%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 tight, well-structured instruction-only skill: every section is actionable, the workflow is unambiguous, and nothing is wasted. The small gaps are a worked example of a store call and guidance for degenerate cases like an empty search result.

Suggestions

Add one short worked example of an agentdb_pattern_store payload (task, reward, success, critique) so the common store case is copy-paste ready.

Note what to do when pattern search returns no similar episodes (e.g., proceed and store the first episode) to close the workflow's feedback-loop gap.

Clarify where the sessionId value comes from, since it is the one required store parameter with no stated source.

DimensionReasoningScore

Conciseness

The body is lean and assumes competence throughout ("Do the task. Keep the retrieved critique in mind.", "Read the critiques, not just the rewards.") with zero padding or explanation of concepts Claude already knows.

5 / 5

Actionability

Concrete tool calls with exact parameter names and values ("k: 3 to 5", "onlySuccesses: true", a two or three sentence critique) plus verbatim CLI commands make this mostly executable; it falls short of level 5 only because no complete example call or stored-episode payload covers the common case.

4 / 5

Workflow Clarity

The retrieve → act → judge → store sequence is clearly laid out and the judge step is an explicit evidence-based checkpoint ("A test suite that passes is evidence; 'it looks right' is not"), but there is no feedback loop for edge cases such as empty search results, so it does not reach level 5.

4 / 5

Progressive Disclosure

The skill is under 50 lines, needs no external references (none exist in the bundle), and is organized into clearly labeled sections including a profile-capability table, which per the rubric's simple-skill guideline earns the top score.

5 / 5

Total

18

/

20

Passed

Description

88%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 description that states concrete capabilities and explicit use-when triggers in third-person imperative style. Its only weaknesses are a few missing natural synonyms and slightly broad memory/self-learning triggers that could overlap with related skills.

DimensionReasoningScore

Specificity

The description lists the full concrete loop — "search similar episodes before a task, record reward, success and critique after it, and read trends" — giving comprehensive, specific coverage rather than minor gaps (level 4).

5 / 5

Completeness

It clearly states what the skill does (search episodes, record reward/success/critique, read trends) and gives an explicit "Use when..." clause with concrete trigger phrases, matching the top anchor exactly.

5 / 5

Trigger Term Quality

Natural phrases like "remember what worked", "pattern store/search", and "self-learning" are present, but common variations such as "learn from experience" or "past episodes" are missing, placing it just below the comprehensive-synonym coverage of level 5.

4 / 5

Distinctiveness Conflict Risk

Naming ReasoningBank and agentic-flow establishes a clear niche, but broad triggers like "wants agents to remember what worked" and "self-learning" create minor overlap risk with generic memory/learning skills, keeping it below minimal-conflict level 5.

4 / 5

Total

18

/

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

ruvnet/agentic-flow

Path

plugins/agentic-flow/skills/reasoningbank-learning/SKILL.md

Reviewed

Table of Contents

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