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self-evolving-single-agent

Use when generating a single installable agent that should keep learning, track sources, refresh research, propose repairs, or improve itself over time without becoming a multi-agent team.

Quality

77%

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SecuritybySnyk

Low

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tessl review fix ./codex/plugins/agentlas-core-engine-meta-agent/runtime-support/skills/self-evolving-single-agent/SKILL.md

The canonical home for this skill is self-evolving-single-agent in agentlas-ai/Agentlas-OS

SKILL.md
Quality
Evals
Security

Quality

Content

65%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 impressively token-efficient and assumes Claude's competence throughout, but it is a compressed checklist rather than an executable guide: the pivotal interview contract and referenced docs/templates do not exist in the bundle, verification is named but never specified, and the final approval section leans on undefined jargon (Curator, legacy chip, evolution-v2) that muddies the workflow. It reads like a summary of a larger skill whose supporting files were never shipped.

Suggestions

Ship the referenced bundle files — at minimum `contracts/builder-interview-research-gate.md` with the 8-12 interview questions and the `.agentlas/*` / `docs/*` templates — or inline their essential contents so the procedure is self-contained.

Replace the bare `verification` output item with 2-3 concrete verification steps (e.g., what to check in the generated package and how to report it) so the workflow has an explicit validation checkpoint.

Rewrite the 'File revision approval' section in plain terms: define what a valid approval receipt is, and either explain or remove undefined terms like 'Curator verdict', 'legacy chip', and 'revision-v1/evolution-v2 host capabilities'.

DimensionReasoningScore

Conciseness

The body is lean with zero padding: no concept explanations, no library background, and every step is a dense directive such as "Run `contracts/builder-interview-research-gate.md` before generation" and "Make self-evolution proposal-first". It fully assumes Claude's competence and every token carries instruction, matching the 'lean and efficient' anchor; there is no verbosity to trim, so it does not fall to 4.

5 / 5

Actionability

There is concrete guidance — exact file names (`docs/builder-interview.md`, `.agentlas/memory-map.json`, `.agentlas/capability-eval-plan.json`), a numbered procedure, and named deliverables — but key details are missing: no commands, no templates, and the invoked `contracts/builder-interview-research-gate.md` (with its 8-12 question interview) has no content anywhere in the bundle. This matches 'some concrete guidance but incomplete; missing key details' rather than the mostly-executable anchor 4.

3 / 5

Workflow Clarity

The Procedure is a clear numbered sequence (interview gate, memory architecture, refresh loop, docs, approval gate, global commands) and an approval checkpoint exists ("wait for human approval"), but validation remains implicit: "verification" appears only as a bare output name with no steps, and the 'File revision approval' section mixes process constraints (Curator verdicts, legacy chips, revision-v1/evolution-v2 host capabilities) that are never defined or sequenced. Checkpoints are named but unspecified, matching anchor 3 rather than 4.

3 / 5

Progressive Disclosure

Sections (Procedure, Output, File revision approval) provide reasonable structure, but the body references paths — `contracts/builder-interview-research-gate.md`, `docs/*`, `.agentlas/*` — and the bundle contains no references/, scripts/, or assets/ directories, so the central interview-research gate contract is a dangling reference with no home. This lands at 'some structure but could be better organized; references present but not clearly signaled' rather than the well-signaled anchor 4.

3 / 5

Total

14

/

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 with an explicit 'Use when...' trigger, several concrete capability phrases, and a clearly demarcated niche that explicitly excludes multi-agent teams. Its main weakness is that the 'what' is embedded in the trigger clause rather than stated as its own capability summary, and a few natural synonyms (e.g., 'self-improving') are absent.

Suggestions

Lead with a short third-person capability statement (e.g., 'Generates a single installable agent package with memory architecture, research refresh, and proposal-first self-evolution.') before the 'Use when...' clause so the 'what' stands on its own.

Add one or two natural synonyms such as 'self-improving' or 'autonomous learning agent' to broaden trigger coverage.

DimensionReasoningScore

Specificity

Names the domain ("generating a single installable agent") and lists several concrete capabilities: "keep learning, track sources, refresh research, propose repairs, or improve itself over time". It falls short of a 5 because the actions are capability-level rather than the concrete operations the skill actually performs (interview gate, memory architecture, docs, approval gates), which leaves minor coverage gaps.

4 / 5

Completeness

The 'when' is explicit and specific ("Use when generating a single installable agent that should keep learning...") and a 'what' is present (generating that agent package), but the what is folded into the trigger clause rather than stated independently. It is above anchor 3 because both elements are present; it is not a 5 because the what-it-does is compressed and less explicit than the when.

4 / 5

Trigger Term Quality

Contains natural phrases a user would plausibly say: "single installable agent", "keep learning", "track sources", "improve itself", "multi-agent team". Not a 5 because common synonyms like "self-improving", "autonomous agent", or "single-agent package" are missing, leaving a few natural terms uncovered.

4 / 5

Distinctiveness Conflict Risk

It carves out a clear niche — a single self-evolving agent — and explicitly demarcates the boundary with "without becoming a multi-agent team", minimizing conflict with general agent-generation or multi-agent orchestration skills. Triggers (self-improvement, research refresh, repair proposals) are distinct enough that mis-triggering risk is minimal.

5 / 5

Total

17

/

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

agentlas-ai/Agentlas-OS

Path

codex/plugins/agentlas-core-engine-meta-agent/runtime-support/skills/self-evolving-single-agent/SKILL.md

Reviewed

Table of Contents

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