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agent-harness-construction

AI エージェントのアクション空間、ツール定義、観測フォーマットを設計・最適化して完了率を向上させます。

Quality

70%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./docs/ja-JP/skills/agent-harness-construction/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

68%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 exceptionally lean, well-structured set of design principles with no wasted tokens and no reliance on external files. Its weaknesses are a lack of concrete, executable artifacts (no example tool schemas or sample responses) and the absence of an explicit application workflow with validation checkpoints.

Suggestions

Add a copy-paste-ready example of a good tool definition (JSON input schema) and a sample tool response/error payload implementing the observation and error-recovery contracts, so the principles become executable.

Present an ordered application workflow with an explicit validation loop, e.g., 1) audit current tool list for semantic overlap, 2) apply granularity rules, 3) reshape observations, 4) benchmark pass@1/pass@3 and iterate if completion rate does not improve.

Consider splitting the architecture-pattern and benchmark sections into a reference file to keep SKILL.md as a tight overview, and add an explicit trigger section aligning with the description's missing 'when' guidance.

DimensionReasoningScore

Conciseness

The body is composed of terse imperatives and checklists ("安定した明示的なツール名を使用する", "フェーズの境界でコンパクト化する") with no padding and no re-explanation of concepts Claude already knows — even the architecture-patterns section gives selection guidance rather than definitions of ReAct or function calling. It matches anchor 5 ("lean and efficient; every token earns its place") and shows nothing to trim that would justify a 4.

5 / 5

Actionability

There is some concrete guidance — the observation contract specifies exact fields (`status: success|warning|error`, `summary`, `next_actions`, `artifacts`) and the error-recovery contract lists required contents — but most rules are abstract directives ("入力スキーマファーストで絞り込んだものにする") with no example tool schemas, sample JSON responses, or copy-paste templates. This matches anchor 3 ("some concrete guidance but incomplete") rather than 4, which requires mostly executable guidance.

3 / 5

Workflow Clarity

Sections are organized by design concern and the numbered lists read as steps, but there is no end-to-end process for applying the skill (no order across sections, no stop conditions, no feedback loop). Benchmarks are presented as a metrics list rather than a validate→fix→re-measure loop, so validation checkpoints are only implicit — matching anchor 3 ("sequence present but checkpoints missing or implicit").

3 / 5

Progressive Disclosure

The skill is a single self-contained file with well-organized headers and no bundle files or references, so there are no deep or broken references. It matches anchor 4 ("good structure; most content appropriately placed") rather than 5 because the body is 68 lines (48 non-blank), slightly exceeding the under-50-line simple-skill exception, and some sections (e.g., architecture patterns, benchmarks) could live in separate reference files.

4 / 5

Total

15

/

20

Passed

Description

58%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.

The description is concise and specific about what the skill does, listing concrete design targets and a measurable outcome, and it occupies a distinct niche. Its main weaknesses are the complete absence of a "Use when..." trigger clause and limited natural trigger-term coverage.

Suggestions

Add an explicit trigger clause, e.g., "Use when building or tuning an AI agent harness, when completion rates are low, or when the user mentions tool definitions, action space, or agent observability."

Include natural trigger terms and synonyms users would actually say (agent harness, tool use, function calling, agentic loop, エージェント設計) so the skill is discoverable from natural phrasing.

Broaden the capability list to cover what the body actually teaches (error recovery contracts, context budget management, benchmarking) for fuller "what" coverage.

DimensionReasoningScore

Specificity

"アクション空間、ツール定義、観測フォーマットを設計・最適化して完了率を向上させます" names several concrete design targets (action space, tool definitions, observation formats) plus a measurable outcome (completion rate). It falls short of anchor 5 because it omits capabilities the body actually covers (error recovery, context budget management, benchmarking), but exceeds anchor 3 by listing multiple specific objects rather than 1-2 generic actions.

4 / 5

Completeness

The description clearly answers "what" (designs/optimizes action space, tool definitions, observation formats to improve completion rate) but contains no "Use when..." clause or equivalent trigger guidance, which the guidelines explicitly cap at 3. It is not a 2 because the "what" is specific and concrete, matching anchor 3 exactly.

3 / 5

Trigger Term Quality

Relevant keywords are present ("AI エージェント", "ツール定義", "完了率") but common natural variations a user would say are missing (e.g., "エージェントハーネス", "function calling", "tool use", "エージェント設計", "プロンプト"). This matches anchor 3 ("some relevant keywords but missing common variations or synonyms") rather than 4, which requires good coverage with only a few gaps.

3 / 5

Distinctiveness Conflict Risk

The niche (designing agent action spaces, tool definitions, and observation formats) is fairly distinct with specific technical triggers, so it matches anchor 4 ("mostly distinct; minor overlap risk"). It is not 5 because it could still overlap with closely related skills such as prompt-engineering or tool-integration skills.

4 / 5

Total

14

/

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

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

affaan-m/ECC

Path

docs/ja-JP/skills/agent-harness-construction/SKILL.md

Reviewed

Table of Contents

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