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session-compact

AI DevKit · Compact a historical AI coding session with Jev when context is long, work is handed off or resumed, or durable continuation facts and memory candidates need extraction.

Quality

91%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

100%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.

The body is an exemplary short skill: executable commands, a clear sequenced workflow with an explicit failure branch, and disciplined boundaries with no filler. Nothing scored below the top anchor.

DimensionReasoningScore

Conciseness

The body is lean and operational throughout: short When-to-Use bullets, direct commands, a quoted error string, and terse boundary statements. No concept explanations or padding appear, and every sentence carries non-obvious operational information, matching the anchor for assuming Claude's competence.

5 / 5

Actionability

All guidance is copy-paste ready ("npx ai-devkit@latest agent sessions --all", "agent session compact --id <session-id> --format json") and covers the common cases: session discovery, Markdown vs JSON output, provider disambiguation, and a quoted unavailability message. This matches the fully-executable anchor.

5 / 5

Workflow Clarity

The five-step workflow is clearly sequenced with an explicit review checkpoint ("Review the artifact before using its resume prompt, memory candidates, or validation claims") and an explicit error-recovery branch (if Jev reports unavailability, stop and report clearly). The operation is read-only and non-destructive, so no destructive-validation cap applies.

5 / 5

Progressive Disclosure

The skill is a single-purpose, ~48-line document with no bundle files (references/, scripts/, assets/ are absent) and no external references. Per the simple-skill guideline, well-organized sections (When to Use, Workflow, Jev Availability, Boundaries) warrant a 5.

5 / 5

Total

20

/

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 explicitly states both what the skill does and multiple natural when-triggers in third person. Its main weaknesses are limited action coverage and a niche that slightly overlaps with generic session-summarization/compaction capabilities.

Suggestions

List one or two more concrete actions or outputs (e.g., produces a structured continuation artifact with a resume prompt, in Markdown or JSON) to lift specificity.

Add natural synonym triggers users might say, such as "summarize the session", "handoff summary", or "session compaction", to broaden trigger-term coverage.

DimensionReasoningScore

Specificity

The description names the domain ("AI DevKit · Compact a historical AI coding session with Jev") and 1-2 concrete actions (compaction, extraction of "durable continuation facts and memory candidates"), matching the anchor for domain plus 1-2 actions. It does not list several distinct actions (e.g., output formats, artifact types), so it falls short of anchor 4.

3 / 5

Completeness

It explicitly answers "what" ("Compact a historical AI coding session with Jev" and extract "continuation facts and memory candidates") and "when" ("when context is long, work is handed off or resumed, or durable continuation facts and memory candidates need extraction") with concrete trigger phrases, matching the anchor-5 example structure.

5 / 5

Trigger Term Quality

Natural phrases like "context is long", "handed off", and "resumed" give good keyword coverage, but there are no synonyms or common variations (e.g., "summarize the session", "handoff summary", "compaction"). This fits anchor 4 (good coverage, a few natural terms missing) rather than anchor 5's comprehensive synonym coverage.

4 / 5

Distinctiveness Conflict Risk

The AI DevKit/Jev framing carves a clear niche, but "Compact a historical AI coding session" overlaps with generic compaction/handoff summarization skills a user might reach for instead. This is minor overlap risk with closely related skills (anchor 4), not the minimal-conflict clarity of anchor 5.

4 / 5

Total

16

/

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

codeaholicguy/ai-devkit

Path

skills/session-compact/SKILL.md

Reviewed

Table of Contents

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