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deep-research

Deep research on any topic using parallel sub-agents and built-in tools only (WebSearch/WebFetch + free APIs, no keys). Use when the user asks for a thorough multi-source investigation with a cited report — "深度调研X"、"deep research"、"帮我全面研究一下"、"多方求证"、"写一份调研报告". NOT for simple lookups (single WebSearch suffices) and NOT for academic literature surveys (use auto-research skill instead).

72

Quality

88%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

77%

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 well-structured, concise, actionable workflow with strong validation checkpoints. However, its three reference files are missing from the bundle and it embeds an author-specific absolute workflow path, breaking the progressive-disclosure contract.

Suggestions

Ship the referenced bundle files (reference/subagent-prompt.md, reference/sources.md, reference/report.md) or remove the dead links — currently every sub-agent prompt, sources list, and report template the body relies on is unreachable.

Replace the hardcoded /Users/mi/claude-workspace/.mimocode/workflows/deep-research-pro.js absolute path with a bundle-relative reference (e.g. scripts/deep-research-pro.js) so the scripted-workflow alternative works in any environment.

Verify each link in the body resolves to a real file before publishing; dangling references force the model to improvise the very templates the skill promises to lock down.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — no explaining what a sub-agent or WebSearch is, tight budget tables, and imperative one-liners like 'Spawn one sub-agent per angle in a single message'. Every token earns its place.

3 / 3

Actionability

Gives concrete executable guidance: a specific `date +%Y-%m-%d` Bash command, a depth-mode table with hard budgets, a directory layout, a verbatim copy-paste `workflow({...})` invocation block, and explicit per-phase file contracts.

3 / 3

Workflow Clarity

A clearly sequenced Step 0 → Phase 1–5 pipeline with explicit validation checkpoints: Phase 4 gap-check against brief.md, 'If a sub-agent fails...note it and move on', a critique pass for deep mode, and resume-from-checkpoint handling — exactly the validate/feedback-loop pattern the rubric rewards.

3 / 3

Progressive Disclosure

The body signals one-level-deep references — [reference/subagent-prompt.md](reference/subagent-prompt.md), [reference/sources.md](reference/sources.md), [reference/report.md](reference/report.md) — but NONE of these files exist in the bundle (no references/, scripts/, or assets/ directory), and it also points to a machine-local absolute path (/Users/mi/...deep-research-pro.js). Per the rubric, progressive_disclosure must be scored against the actual bundle structure; dangling, non-existent references are the worst case.

1 / 3

Total

10

/

12

Passed

Description

100%

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, third-person description that clearly states capabilities, gives natural multilingual trigger terms, and uses explicit positive and negative triggers to bound scope. It would naturally surface for the right request and avoid the wrong ones.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'parallel sub-agents', 'WebSearch/WebFetch + free APIs', 'cited report' — naming both the mechanism and the output, matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers both what ('Deep research...using parallel sub-agents and built-in tools only') and when ('Use when the user asks for a thorough multi-source investigation with a cited report'), plus explicit negative triggers ('NOT for simple lookups...', 'NOT for academic literature surveys').

3 / 3

Trigger Term Quality

Includes natural trigger phrases users would actually say across languages — '深度调研X', 'deep research', '帮我全面研究一下', '多方求证', '写一份调研报告' — giving strong coverage of common variations.

3 / 3

Distinctiveness Conflict Risk

The 'NOT for simple lookups' and 'NOT for academic literature surveys (use auto-research skill instead)' carve-outs establish a clear niche and actively prevent conflicts with adjacent skills.

3 / 3

Total

12

/

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

relative_links

Relative link issues: 3 missing

Warning

Total

15

/

16

Passed

Repository
XiaomiMiMo/MiMo-Code
Reviewed

Table of Contents

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