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agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent's tool set, action space, or observation format.

66

Quality

83%

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SKILL.md
Quality
Evals
Security

Quality

Content

76%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 exceptionally token-efficient with concrete, field-level design rules, but it reads as a static checklist rather than an applicable workflow: no sequenced audit-to-benchmark loop, no validation checkpoints, and no worked examples. Structure is good for a single-file skill.

Suggestions

Add a short sequenced workflow (audit existing tools → apply action-space/observation rules → benchmark → iterate) so the guidance functions as a process with feedback rather than a static checklist.

Include one worked example contrasting a good tool definition/response shape with an anti-pattern to make the observation and action-space rules directly applicable.

Tie the Benchmarking metrics back into revision guidance (e.g., 'if retries per task rises, split the catch-all tool') to close the feedback loop.

DimensionReasoningScore

Conciseness

The body is a lean, checklist-style reference with zero padding and no explanations of concepts Claude already knows (e.g., "Keep inputs schema-first and narrow", "Compact at phase boundaries, not arbitrary token thresholds"); every token earns its place.

5 / 5

Actionability

Guidance is concrete and checkable — e.g., "Every tool response should include: `status`, `summary`, `next_actions`, `artifacts`" — but there are no worked examples (such as a good vs. bad tool definition) to anchor application, so it falls short of the fully executable 5 anchor while exceeding the pseudocode-level 3 anchor.

4 / 5

Workflow Clarity

Sections are organized by concern rather than as a sequenced process: there is no explicit apply workflow (audit existing tools → redesign → benchmark → iterate) and no feedback loop tying the "Benchmarking" metrics back into revision, matching the "steps listed but checkpoints missing" anchor.

3 / 5

Progressive Disclosure

No bundle files exist and the ~65-line body is well-sectioned, but it slightly exceeds the under-50-line simple-skill exception and material like architecture patterns and benchmarking could arguably be split into references, placing it just below the 5 anchor.

4 / 5

Total

16

/

20

Passed

Description

83%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 covers both what the skill does and when to use it, with domain-specific trigger terms and low conflict risk. Main weakness is modest breadth of concrete action verbs and missing synonyms in the trigger phrasing.

DimensionReasoningScore

Specificity

Lists several concrete actions — "Design and optimize AI agent action spaces, tool definitions, and observation formatting" — but "design and optimize" is somewhat abstract and coverage of the domain's actions is narrower than a comprehensive 5-anchor example; clearly above naming only 1-2 actions.

4 / 5

Completeness

Explicitly answers both what ("Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates") and when ("Use when defining or revising an agent's tool set, action space, or observation format") with concrete trigger phrases, matching the 5 anchor.

5 / 5

Trigger Term Quality

Good natural keywords ("tool set", "tool definitions", "action space", "observation format") that users revising an agent's tools would say, but synonyms like "tool schemas", "prompts", or "MCP tools" are missing, so it falls short of comprehensive 5-anchor coverage while being well above the 3 anchor.

4 / 5

Distinctiveness Conflict Risk

The agent-harness niche (action spaces, observation formatting) is mostly distinct with concrete triggers, but there is minor overlap risk with adjacent prompt-engineering and general agent-design skills, keeping it below the clear-niche 5 anchor.

4 / 5

Total

17

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository

affaan-m/ECC

Path

skills/agent-harness-construction/SKILL.md

Reviewed

Table of Contents

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