Agent skill

Ccf Idea Reviewer

by mikubaka88 in mikubaka88/CCFA-Skills

Assess research ideas for value, novelty, insight, and mechanism.

MITAuto-check passedResearch & Science

Install Ccf Idea Reviewer

skills CLI
$ npx skills add mikubaka88/CCFA-Skills --skill ccf-idea-reviewer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mikubaka88/CCFA-Skills ccf-idea-reviewer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mikubaka88/CCFA-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ccf-idea-reviewer .claude/skills/ccf-idea-reviewer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ccf-idea-reviewer
GitHub stars
3k
Token cost
~2.1k tokens
SKILL.md length
904 words
Files
7 (incl. references)
Skills in repo
17
Repo updated
First seen
Licence
MIT

At a glance

Assess research ideas for value, novelty, insight, and mechanism.

  • Works in 7 steps: Identify the requested judgment,… → Load references/strict-idea-review.md… → Ground decisive novelty claims through… → …
  • No numeric-score request is needed
  • SKILL.md covers Family File Contract, Collaboration Contract, Invocation Controls and Core Rule, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ccf Idea Reviewer is an agent skill from mikubaka88/CCFA-Skills. Assess research ideas for value, novelty, insight, and mechanism. Use for 思路审核, 靠谱吗, 值得做吗, 创新够不够, idea review, scoring, and ranking; no numeric-score request is needed. Default to concept-only review without experiment assessment, including ideas extracted from manuscripts. Developing an idea belongs to ccf-idea-optimizer; evaluating manuscript evidence or writing belongs to ccf-paper-reviewer.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `agents/openai.yaml`, `references/calibration.md` and `references/expert-panel.md`).

It sits in Research & Science, covering Hypothesis generation. The repository describes itself as: A skill family for shaping the research storyline of CCF-A papers. The licence is MIT.

When your agent uses it

  • No numeric-score request is needed
  • Tasks that involve Hypothesis generation

Example prompts

  • “/ccf-idea-reviewer”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Identify the requested judgment, concept, audience, available sources, and any explicit scope extension. Reuse conversation context; ask…
  2. Load references/strict-idea-review.md for report selection and assessment, including qualitative judgments. Normalize problem → gap →…
  3. Ground decisive novelty claims through public-safe retrieval under ../ccf-common/references/privacy-and-evidence.md, unless browsing is…
  4. Assess distinct conceptual perspectives using references/expert-panel.md; combine duplicate issues under stable IDs. Experiment reviewers…
  5. For standard scoring, load references/rubric.md, references/calibration.md, and ../ccf-common/references/review-output-standards.md. Use…
  6. Distinguish decisive conceptual flaws from repairable gaps and unanswered questions. Compare multiple ideas under a common scope and…
  7. For a user-requested review, deliver the detailed report from strict-idea-review.md by default; use its brief version only for an explicit…

What it can do on your machine

Read from SKILL.md and the folder at commit 5969e6b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ccf Idea Reviewer loads about 2.1k tokens when it runs, and up to ~7k if it reads all its reference files. Until then it costs about 104 tokens; SKILL.md has 904 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~104
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mikubaka88/CCFA-Skills at commit 5969e6b, republished under its MIT licence (© mikubaka88). 904 words, ~2,071 tokens.

Download SKILL.mdSave it as .claude/skills/ccf-idea-reviewer/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
ccf-idea-reviewer
description
Assess research ideas for value, novelty, insight, and mechanism. Use for 思路审核, 靠谱吗, 值得做吗, 创新够不够, idea review, scoring, and ranking; no numeric-score request is needed. Default to concept-only review without experiment assessment, including ideas extracted from manuscripts. Developing an idea belongs to ccf-idea-optimizer; evaluating manuscript evidence or writing belongs to ccf-paper-reviewer.

CCF Idea Reviewer

Family File Contract

Before writing, resolve the canonical output and one stable working directory per task/artifact. Reuse explicit or established task paths; otherwise use project-root ccfa-workfiles/<purpose>/<artifact-id>/, with source/, assets/, cache/, and build/ only as needed. Update current files in place; do not scatter intermediates or create iteration copies. Preserve inputs and required evidence; clean only verified disposable files created by this task. Use UTF-8 text I/O and check Chinese text after saving or rendering. For file work, apply artifact-contracts.md and reuse the same paths across skill transitions.

Collaboration Contract

Before specialist execution, read and apply ccf-humanization first, then ccf-common. At every handoff, reuse their applicable active rules or refresh missing/changed ones. Both preflights are required even without prose; detailed editing, experiment, and maintenance modes run only when relevant.

Keep one integrating owner and actively use other skills to resolve missing prerequisites or check material findings. Reuse applicable evidence; do not skip necessary groundwork to save tokens. Before finalizing, integrate contributions and verify affected results. Follow the conditional cooperation routes; avoid unrelated stages and duplicate reports.

Invocation Controls

CCFA Handoff Mode: PARTIAL (Recommended). Follow metadata.ccf_skill_controls.handoff_question_mode, ../ccf-common/references/handoff-modes.md, and ../ccf-common/references/task-modes.md. Infer assessment from the requested judgment; an exact skill name, review keyword, or numeric score is unnecessary. A rough idea can still receive a serious concept assessment.

Choose by the object of judgment, not file type: a PDF supplied for “只看核心思路” remains idea review. Use ccf-idea-optimizer for requested development and ccf-paper-reviewer for manuscript evidence, scientific completeness, writing, or version readiness. Execute an explicitly combined review/development task through its respective owners without another permission round.

Core Rule

Judge problem importance, novelty against closest work, conceptual insight, mechanism coherence, elegance, and audience fit. Default to concept-only scope. Do not grade experiments, demand baselines/ablations/results, assess implementation resources, or lower the verdict because research is unfinished. Add experiment or feasibility assessment only when the user requests that extension, keeping it separate from the concept score.

Distinguish a logical contradiction from an untested hypothesis. A meaningful claim can be assessed before experimental validation. Separate concept quality, development potential, and confidence; do not turn uncertain novelty into demonstrated overlap or submission readiness into idea quality.

Every consequential criticism identifies the affected idea statement or assumption, its inspected basis, its significance, and the smallest repair. Do not fabricate prior art, results, reviewer agreement, or acceptance probability. Use abandon only after identifying why no meaningful formulation or plausible rescue remains.

Workflow

For an internal contribution, run the checks needed for its assigned conceptual question and evidence dependencies, then return findings under the internal output contract. The complete workflow and report apply to a user-requested idea review.

  1. Identify the requested judgment, concept, audience, available sources, and any explicit scope extension. Reuse conversation context; ask only for a missing decision that changes the assessment. Do not ask for experimental materials merely to start idea review.
  2. Load references/strict-idea-review.md for report selection and assessment, including qualitative judgments. Normalize problem → gap → insight → mechanism; keep experimental planning outside default intake.
  3. Ground decisive novelty claims through public-safe retrieval under ../ccf-common/references/privacy-and-evidence.md, unless browsing is forbidden. Use ccf-literature-searcher to resolve missing closest-work evidence and integrate its mechanism comparison before the verdict. Reuse applicable verified sources and record searched, partially searched, supplied-only, or unsearched coverage. Inspect relevant primary-source content before claiming overlap; missing experimental results are not a concept-review prerequisite.
  4. Assess distinct conceptual perspectives using references/expert-panel.md; combine duplicate issues under stable IDs. Experiment reviewers are optional for a requested extension. Use independent calls only if permitted and useful, and label single-agent perspectives honestly.
  5. For standard scoring, load references/rubric.md, references/calibration.md, and ../ccf-common/references/review-output-standards.md. Use the six conceptual dimensions and assessed-weight coverage. Honor no-score requests with qualitative judgments; low confidence is not a low score.
  6. Distinguish decisive conceptual flaws from repairable gaps and unanswered questions. Compare multiple ideas under a common scope and rubric. Re-review changed assumptions and unresolved concerns without imposing new experiment criteria.
  7. For a user-requested review, deliver the detailed report from strict-idea-review.md by default; use its brief version only for an explicit brevity request or restrictive user format. Put requested optimization or experiment work in its own authorized deliverable.
Show full SKILL.md (216 more words)Show less

Output Contract

For a bounded internal concept check requested by another skill, return the inspected concept, evidence-backed findings, unresolved questions, and completion conditions to its owner. Do not create a standalone score report or develop a replacement idea. A user-requested idea review retains the report requirements below, including its detailed default and concept-only scope.

Use the concept-review structure defined in references/strict-idea-review.md; do not substitute a generic coaching response or manuscript acceptance report. State the conceptual verdict, prior-art delta, anchored concerns, applicable scorecard, development potential, confidence, and concrete refinements without repeating the same criticism. A rough seed, short prompt, or no-score request does not select brief output or authorize experiment assessment.

For an explicitly requested brief judgment, use the template's five blocks and retain the same concept-only boundary. No forced scores or experimental checklist. Recommendations remain accept-to-develop, revise, pivot-with-rescue-route, abandon, or needs-literature-search.

References

  • references/strict-idea-review.md: standard report structure, grounding, and scope.
  • references/rubric.md, references/calibration.md: concept dimensions, weights, coverage, and decision conditions.
  • references/expert-panel.md: distinct conceptual perspectives and optional requested extensions.
  • references/source-notes.md: public provenance and reuse boundaries.
  • ../ccf-common/references/review-output-standards.md: evidence, scoring, and concern continuity.

For file outputs, follow ../ccf-common/references/artifact-contracts.md: reuse the established report path, keep intermediate files under one stable task directory, and update current files in place. Load this policy only when writing files and it is not already in context.

© mikubaka88, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (references) in ccf-idea-reviewer of mikubaka88/CCFA-Skills.

  • SKILL.md
  • agents/openai.yaml
  • references/calibration.md
  • references/expert-panel.md
  • references/rubric.md
  • references/source-notes.md
  • references/strict-idea-review.md

Open the folder on GitHubat commit 5969e6b

Compare with similar skills

Ccf Idea Reviewer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Ccf Idea Reviewer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ccf Idea Reviewer this skillmikubaka88/CCFA-Skills3k—~2.1kAutomated safety check: PassMIT
Hypothesis Generationspacering-net/codeg3.9k14 repos~3.6kAutomated safety check: NotesMIT
Nature Paper CardYuan1z0825/nature-skills47k2 repos~2.1kAutomated safety check: PassApache-2.0
Hypothesis GenerationK-Dense-AI/claude-scientific-writer2.4k2 repos~3.9kAutomated safety check: PassMIT
Good QuestionRimagination/good-question3051 repos~4.3kAutomated safety check: PassMIT
High Stakes Analytics Decision Lablimingrui679-design/high-stakes-analytics-decision-lab1k—~2.2kAutomated safety check: PassMIT

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Questions about Ccf Idea Reviewer

What does Ccf Idea Reviewer do?

Assess research ideas for value, novelty, insight, and mechanism. Ccf Idea Reviewer is an agent skill from mikubaka88/CCFA-Skills. Assess research ideas for value, novelty, insight, and mechanism.

When should I use Ccf Idea Reviewer?

Ccf Idea Reviewer fits situations like: no numeric-score request is needed; tasks that involve Hypothesis generation.

How do I install Ccf Idea Reviewer in Claude Code?

Run `npx skills add mikubaka88/CCFA-Skills --skill ccf-idea-reviewer -a claude-code`. Or copy the skill folder (ccf-idea-reviewer in mikubaka88/CCFA-Skills) into .claude/skills/ccf-idea-reviewer in your project. Claude Code loads it when a task matches its description.

How do I install Ccf Idea Reviewer in Codex?

Run `npx skills add mikubaka88/CCFA-Skills --skill ccf-idea-reviewer -a codex`. Or copy the skill folder (ccf-idea-reviewer in mikubaka88/CCFA-Skills) into .agents/skills/ccf-idea-reviewer in your project. Codex loads it when a task matches its description.

Can I use Ccf Idea Reviewer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mikubaka88/CCFA-Skills --skill ccf-idea-reviewer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ccf-idea-reviewer, .gemini/skills/ccf-idea-reviewer, .github/skills/ccf-idea-reviewer and .opencode/skills/ccf-idea-reviewer in your project.

What does Ccf Idea Reviewer need to run?

SKILL.md names no scripts, command-line tools or credentials: Ccf Idea Reviewer is instructions for the agent only.

Does Ccf Idea Reviewer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ccf Idea Reviewer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ccf Idea Reviewer use?

Ccf Idea Reviewer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ccf Idea Reviewer use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5k tokens, read only when the agent opens those files.

What are the alternatives to Ccf Idea Reviewer?

Skills that share tags, products or a category with Ccf Idea Reviewer: Hypothesis Generation (spacering-net/codeg, 3.9k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars), Hypothesis Generation (K-Dense-AI/claude-scientific-writer, 2.4k stars) and Good Question (Rimagination/good-question, 305 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ccf Idea Reviewer?

mikubaka88 (a GitHub user) maintains it in mikubaka88/CCFA-Skills, which has 3,015 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on September 16, 2026.

Source: mikubaka88/CCFA-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.