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Ccf Idea Reviewer

CommunityPopular
mikubaka88
ccf-idea-reviewer

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.

Overview

Publishermikubaka88
RepositoryCCFA-Skills
Skill nameccf-idea-reviewer
Stars
2.6K
Forks
116
Bundled files
6
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mikubaka88 on GitHub. Read the source before you install it.

Installation

Install the Ccf Idea Reviewer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mikubaka88/CCFA-Skills.git /tmp/CCFA-Skills
mkdir -p .claude/skills
cp -r /tmp/CCFA-Skills/ccf-idea-reviewer .claude/skills/ccf-idea-reviewer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ccf Idea Reviewer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ccf Idea Reviewer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ccf Idea Reviewer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ccf Idea Reviewer AI skill do?

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.

Why use Ccf Idea Reviewer on TypingMind?

Because you install it once and use it with any model. Ccf Idea Reviewer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ccf Idea Reviewer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mikubaka88/CCFA-Skills/tree/main/ccf-idea-reviewer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ccf Idea Reviewer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ccf Idea Reviewer?

As many as you like. As long as a model supports skills, you can use Ccf Idea Reviewer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ccf Idea Reviewer AI skill free?

Yes. It is published on GitHub by mikubaka88 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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