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research-deep

读取调研outline,为每个item启动独立agent进行深度调研。禁用task output。

56

Quality

63%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/research-zh/research-deep/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%Weight 40%Scale 1-3

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

The workflow is highly actionable and clearly sequenced with the validation and resume checkpoints a batch research job needs. The main weakness is token efficiency, driven by the duplicated one-shot example.

Suggestions

Collapse the one-shot example into a brief inline illustration or move it to a reference file, since it repeats the template structure almost verbatim.

Consider extracting the prompt template to a referenced file (e.g. prompt_template.md) with a clear link, keeping only the variable bindings inline.

Tighten the Agent配置 and Step 4 sections, which partly restate constraints already implied by the prompt and batch gating.

DimensionReasoningScore

Conciseness

The body is mostly tight and assumes Claude's competence, but the ~25-line one-shot example largely duplicates the prompt template and could be tightened.

2 / 3

Actionability

It gives a complete executable f-string prompt, explicit parameter bindings, slugify rules, and a concrete validation command — fully copy-paste ready.

3 / 3

Workflow Clarity

Steps 1–5 are clearly sequenced with a validation checkpoint ('验证通过后才算完成任务'), user-gated batch progression, and resume-skip logic — appropriate feedback loops for a batch operation.

3 / 3

Progressive Disclosure

Sections are well organized with no nested references, but the prompt template and one-shot example are kept inline rather than split into a reference file with signaled navigation.

2 / 3

Total

10

/

12

Passed

Description

50%Weight 40%Scale 1-3

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 the core capability clearly but stops short of stating when it should be invoked and relies on somewhat technical vocabulary. It is competent but not exemplary.

Suggestions

Add an explicit 'Use when...' clause stating the trigger conditions (e.g., when the user wants batch deep research over an outline's items).

Replace internal jargon ('task output', 'outline') with the natural terms a user would actually say, and surface 'Use when' variants.

Concretize '深度调研' by listing the specific outputs it produces (structured JSON per item with field validation).

DimensionReasoningScore

Specificity

It names the domain and concrete actions — '读取调研outline', '为每个item启动独立agent进行深度调研', '禁用task output' — but '深度调研' is abstract and the action set is not comprehensive.

2 / 3

Completeness

It states what the skill does but gives no 'Use when...' trigger guidance, so per the judging guidelines completeness is capped at 2.

2 / 3

Trigger Term Quality

'调研'/'深度调研' is a natural term a user might say, but coverage is thin and 'outline'/'task output' read as internal jargon rather than common user phrasings.

2 / 3

Distinctiveness Conflict Risk

The outline-driven, per-item batch-research niche is fairly distinct, yet it could still overlap with general research skills without a sharper trigger.

2 / 3

Total

8

/

12

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

Total

15

/

16

Passed

Repository
Weizhena/Deep-Research-skills
Reviewed

Table of Contents

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