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agenthub

Run several agents on one task in parallel and keep the best result: faster code, copy variants, research angles. Use whenever the user wants multiple attempts compared or best of N; spawns agents in git worktrees, ranks and merges the winner.

Quality

82%

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SKILL.md
Quality
Evals
Security

Quality

Content

75%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-engineered skill body: dense tables, executable commands with realistic flags, a clearly sequenced coordinator lifecycle, and proper offloading of conceptual depth (templates, coordination patterns, DAG theory) to real one-level-deep reference files. Remaining gaps are a missing post-merge verification step and a slightly muddled tail section where a dry-run command is listed as if it were a reference document.

Suggestions

Add an explicit post-merge verification step to the Merge phase (e.g. re-run the eval command or test suite on the base branch after `git merge --no-ff`, and roll back the tag if it fails).

Create the baseline explicitly in the Init step (the "No improvement over baseline" proactive trigger depends on it), e.g. run the eval command on the base branch before spawning.

Move `python3 scripts/dry_run.py --help` out of the "More in this skill" reference list into the Scripts table (or a Validation section) so that section contains only loadable references.

DimensionReasoningScore

Conciseness

The body is dense and table-driven with concrete commands and no tutorial-style explanation of concepts Claude already knows; concept material (e.g. "Git's commit history is a DAG") is correctly offloaded to references. Not a 5: a 10-item trigger-phrase list duplicates the description's job, and lines like "Equivalent to AgentHub's 'leaves' query" add little.

4 / 5

Actionability

Concrete, mostly copy-paste-ready guidance throughout: `python scripts/result_ranker.py --session {id} --eval-cmd "pytest bench.py --json" --metric p50_ms --direction lower`, `git merge --no-ff`, `git tag hub/archive/{session}/agent-{i}`, a complete agent dispatch prompt, and a full board post format. Not a 5: slash commands like `/hub-init` and `/agenthub:spawn` are never shown with example arguments, and one status command appears without the `python scripts/` prefix.

4 / 5

Workflow Clarity

The INIT → DISPATCH → MONITOR → EVALUATE → MERGE lifecycle is clearly sequenced with numbered phases, a state-transition table, and a proactive-triggers table providing failure feedback loops (all crashed → retry with different constraints; stuck session → check board, consider timeout). Not a 5: there is no post-merge verification (e.g. run tests on the merged result), and the "No improvement over baseline" trigger references a baseline that the Init step never explicitly establishes.

4 / 5

Progressive Disclosure

The body is an overview with well-signaled one-level-deep references that all resolve to real bundle files (agent-templates.md, coordination-strategies.md, dag-patterns.md) plus a scripts table covering 5 of the 6 scripts. Not a 5: the "More in this skill" list ends with a command (`python3 scripts/dry_run.py --help`) masquerading as a loadable reference, and dry_run.py is missing from the Scripts table — minor navigation confusion.

4 / 5

Total

16

/

20

Passed

Description

80%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 states what the skill does (parallel agents, worktree isolation, ranking, merging the winner) and gives an explicit "Use whenever" trigger clause with natural phrases like "multiple attempts compared" and "best of N". The main gap is trigger coverage: several natural variants (fan-out, tournament, A/B test drafts) are omitted even though the skill body lists them.

Suggestions

Broaden the when-clause with the natural variants already listed in the body, e.g. "...or asks to fan out, run a tournament of approaches, or A/B test drafts/copies".

Keep the parallel-agents framing anchored to the distinctive part ("keep the best result" / "best of N") so it does not read as a generic subagent-spawning skill.

DimensionReasoningScore

Specificity

"Run several agents on one task in parallel", "spawns agents in git worktrees, ranks and merges the winner" lists multiple concrete actions covering the full spawn → rank → merge lifecycle, plus use domains ("faster code, copy variants, research angles"). Not a 4: coverage of the core lifecycle is comprehensive rather than having minor gaps.

5 / 5

Completeness

Both parts are explicit: the what ("Run several agents on one task in parallel and keep the best result... spawns agents in git worktrees, ranks and merges the winner") and the when ("Use whenever the user wants multiple attempts compared or best of N"). Not a 5: the when-clause lists only two trigger conditions where the anchor-5 example covers a fuller set of concrete trigger variants.

4 / 5

Trigger Term Quality

"Use whenever the user wants multiple attempts compared or best of N" gives good natural trigger phrases users would actually say. Not a 5: common variations the body itself lists ("fan-out", "tournament", "A/B test", "try multiple approaches") are absent from the description.

4 / 5

Distinctiveness Conflict Risk

The niche is clear — "keep the best result", "best of N", "ranks and merges the winner" — and unlikely to trigger for unrelated skills. Not a 5: the opening "Run several agents on one task in parallel" is generic fan-out language that overlaps with general multi-agent/subagent orchestration skills.

4 / 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

alirezarezvani/claude-skills

Path

engineering/agenthub/skills/agenthub/SKILL.md

Reviewed

Table of Contents

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