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retrospect-collab

Analyze collaboration patterns (HOW) and compute metrics from captured sessions. Use when reviewing collaboration quality, analyzing human-AI interaction, computing session metrics. Triggers include "retrospect collab", "collaboration analysis", "session patterns", "how am I collaborating".

Quality

81%

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SKILL.md
Quality
Evals
Security

Quality

Content

78%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 well-structured skill body: executable commands, a clear step sequence with error handling for the batch session-read, and proper use of a single clearly-labeled reference file. The only refinements are trimming the role/usage padding and moving error-handling notes inline as validation checkpoints.

DimensionReasoningScore

Conciseness

The body is efficient: it assumes Claude's competence (no explanation of what retrospectives or collaboration analysis are), keeps analysis dimensions as terse bullet lists, and uses justified anti-pattern WHY clauses. Minor trimmable parts remain — the 'Role' expertise line and four usage examples that restate the argument-hint — placing it at efficient-with-minor-trimming rather than every-token-earns-its-place.

4 / 5

Actionability

Concrete executable guidance dominates: an exact loader command with parse instructions ('First line: PERIOD...'), a copy-ready Metrics Summary format block, an explicit output path pattern, and runnable slash-command examples. Minor gaps remain — steps 3-4's analysis criteria are directive rather than fully concrete, and impact-percentage computation details are delegated to the reference file.

4 / 5

Workflow Clarity

The 7-step sequence is clear and ordered, and the batch-read operation has explicit failure handling: the PERIOD-header parse warning, skipping missing duration_seconds instead of erroring, and producing a partial report for unreadable session files. It falls short of level 5 because these checkpoints live in a separate Gotchas section rather than being sequenced inline as validate-then-proceed steps (e.g., verify the session count against the filter before analyzing).

4 / 5

Progressive Disclosure

The body is a well-sectioned overview (When to Use / When Not to Use / Principles / Steps / Gotchas) with a single one-level-deep bundle file, references/reference.md, which exists and is clearly signaled with its contents named ('scoring rubrics, metric definitions, and report format'). Core behavioral rules and the short metrics template stay in SKILL.md while the full report template and rubric detail are pushed to the reference — an appropriate split with easy navigation.

5 / 5

Total

17

/

20

Passed

Description

78%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 clearly answers what the skill does and when to use it, with genuinely natural trigger phrases including the exact question a user would ask. The main gap is specificity: the computed metrics are only vaguely gestured at rather than named.

Suggestions

Name the concrete metrics in the description (e.g., 'categorize sessions as Automation / Low-impact / High-impact augmentation and compute prompt, tool-call, and duration aggregates') to lift specificity from naming 2 actions to several concrete capabilities.

Add the HOW-vs-WHAT boundary to the description (e.g., 'Use retrospect-domain when the focus is what was learned') to reduce overlap risk with the sibling skill at the description level.

DimensionReasoningScore

Specificity

The description names the domain and two concrete actions — "Analyze collaboration patterns (HOW)" and "compute metrics from captured sessions" — matching the anchor for 1-2 concrete actions without comprehensive coverage. It never says which metrics are computed (e.g., the Automation/Low-impact/High-impact breakdown), which keeps it below the 'several specific actions' of level 4.

3 / 5

Completeness

It explicitly answers both parts: what ("Analyze collaboration patterns (HOW) and compute metrics from captured sessions") and when ("Use when reviewing collaboration quality, analyzing human-AI interaction, computing session metrics"), followed by concrete trigger phrases in quotes. This matches the anchor that clearly answers both what and when with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural phrases users would actually say are well covered: "how am I collaborating", "collaboration analysis", "session patterns", plus "retrospect collab" for the command form. A few natural synonyms are missing (e.g., "retrospective", "working with AI", "AI collaboration quality"), which fits good-but-not-comprehensive keyword coverage rather than level 5.

4 / 5

Distinctiveness Conflict Risk

The HOW-focused collaboration framing with distinct trigger phrases carves a clear niche and is unlikely to fire for unrelated skills. Minor overlap risk remains with the sibling `retrospect-domain` skill (which reviews the same captured sessions for WHAT was learned), since the description itself doesn't state that boundary — it is only in the body — so it sits just below the minimal-conflict level 5.

4 / 5

Total

16

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository

pantheon-org/tekhne

Path

skills/specialized/retrospect-collab/SKILL.md

Reviewed

Table of Contents

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