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openclaw-mission-control

Coordinate AI agent teams via a Kanban task board with local JSON storage. Enables multi-agent workflows with a Team Lead assigning work and Worker Agents executing tasks via heartbeat polling. Perfect for building AI agent command centers.

78

3.41x
Quality

Does it follow best practices?

Impact

99%

3.41x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

65%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is highly actionable with executable commands and clear sequencing, but it is verbose and monolithic with no bundle references, and it lacks validation checkpoints for destructive/batch operations. A broken nested code fence in the heartbeat section further degrades clarity.

Suggestions

Add validation/verification checkpoints (e.g., confirm a task exists and its status before DELETE or status transitions; verify /api/seed created all agents) to support the destructive/batch operations.

Fix the broken nested markdown fencing in the heartbeat section (lines 162-215) so all five steps render inside the intended block.

Move the full API reference and config examples into bundled reference files and link them one level deep to slim the SKILL.md overview.

DimensionReasoningScore

Conciseness

The body is comprehensive and mostly efficient, but ~470 lines largely document an external app's full API surface and config inline, which could be tightened and partly moved to bundled reference files.

2 / 3

Actionability

Concrete, executable curl/git/npm commands and full config examples appear throughout, making most sections copy-paste ready, matching the anchor for fully executable guidance.

3 / 3

Workflow Clarity

Steps are clearly sequenced (Quick Start, lifecycle, example workflow), but batch/destructive operations like task DELETE and /api/seed have no validation/verification checkpoints, which caps workflow clarity at 2 per the rubric.

2 / 3

Progressive Disclosure

No bundle files exist and everything is inlined in one monolithic document, with a large API reference and full config that could be split into separate referenced files; no deeply nested references, so it is not a 1.

2 / 3

Total

9

/

12

Passed

Description

67%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description conveys concrete capabilities and a distinct niche clearly, but omits any explicit 'when to use' trigger guidance and leans on some technical jargon, which limits trigger-term quality and completeness.

Suggestions

Add an explicit 'Use when ...' clause naming natural user phrasings (e.g., coordinating AI agents, multi-agent task boards, agent heartbeat polling).

Soften jargon like 'heartbeat polling' with plain-language variations users would actually say.

Tighten the marketing phrase 'Perfect for building AI agent command centers.' which adds little trigger signal.

DimensionReasoningScore

Specificity

Names multiple concrete actions — 'Coordinate AI agent teams via a Kanban task board with local JSON storage', 'assigning work', 'executing tasks via heartbeat polling' — matching the anchor for several specific concrete actions.

3 / 3

Completeness

It clearly answers 'what does this do' but provides no 'Use when...' clause or equivalent explicit trigger guidance, capping completeness at 2 per the rubric guideline.

2 / 3

Trigger Term Quality

Relevant keywords like 'AI agent teams', 'multi-agent workflows', and 'Kanban task board' appear, but 'heartbeat polling' is jargon and common natural-language variations are missing.

2 / 3

Distinctiveness Conflict Risk

The combination of 'Kanban task board', 'heartbeat polling', and 'multi-agent workflows' carves a clear niche unlikely to trigger for unrelated skills.

3 / 3

Total

10

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
NeverSight/skills_feed
Reviewed

Table of Contents

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