Agent skill

NSFC Application Audit

by jiankang1991 in jiankang1991/nsfc-benzi-audit

Diagnoses a draft Chinese NSFC grant application for the applicant, pointing out logic breaks, weak evidence and high-impact fixes, calibrated to the application year and form.

MITAuto-check passedResearch & Science

Install NSFC Application Audit

skills CLI
$ npx skills add jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-audit -a claude-code

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

GitHub CLI
$ gh skill install jiankang1991/nsfc-benzi-audit nsfc-benzi-audit --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/jiankang1991/nsfc-benzi-audit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/nsfc-benzi-audit .claude/skills/nsfc-benzi-audit && 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
nsfc-benzi-audit
GitHub stars
108
Token cost
~2.5k tokens
SKILL.md length
1,212 words
Files
14 (incl. references, assets)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Diagnoses a draft Chinese NSFC grant application for the applicant, pointing out logic breaks, weak evidence and high-impact fixes, calibrated to the application year and form.

  • Works in 6 steps: Select the source and establish the… → Load the relevant references. → Build the logic and evidence maps. → …
  • Getting a logic and evidence check on an NSFC application draft before submission
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Re-auditing a revised draft after changing the scientific question

What it does

The agent accepts PDF, DOCX, Markdown or plain text and checks the title, abstract, rationale, key scientific questions, research contents, innovation, feasibility, research basis and consistency across sections. It starts by choosing the right source: the draft you name rather than the largest file, with funded examples, old reports and templates kept apart, and extracted text matched to the original. It records the application year, exact project category, form version, funding mode, research attribute and application code, and inspects original figures when judging evidence.

Advice stays grounded in the supplied draft. The agent must not fabricate literature, results, budgets or official requirements, and it treats missing attachments or failed extraction as gaps, not confirmed defects. A quick pass covers the headline sections, a full diagnosis covers everything supplied, and a focused request stays on one chapter or question. It does not write applications from scratch or give formal expert-review opinions. References cover audit surfaces, question distillation, representative works, current rules and field notes for geospatial, information and biomedical topics, plus a report template.

When your agent uses it

  • Getting a logic and evidence check on an NSFC application draft before submission
  • Re-auditing a revised draft after changing the scientific question
  • Comparing a draft's structure against a funded example

Example prompts

  • “Audit my 2026 NSFC Youth application draft in ./drafts/proposal.docx and list the biggest logic gaps.”
  • “Do a quick pass on the title, abstract and scientific questions of this proposal PDF.”
  • “Check whether my representative works actually support the key scientific question in section two.”

Requirements

  • PDF or DOCX text extraction or OCR tools, when the draft is not plain text

Workflow steps

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

  1. Select the source and establish the review scope.
  2. Load the relevant references.
  3. Build the logic and evidence maps.
  4. Recheck prior findings when a prior report/list is supplied in files or chat.
  5. Diagnose by impact and give concrete actions.
  6. Write the report and preserve its evidence trail.

What it can do on your machine

Read from SKILL.md and the folder at commit 9a6010b. 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

NSFC Application Audit loads about 2.5k tokens when it runs, and up to ~41k if it reads all its reference files. Until then it costs about 127 tokens; SKILL.md has 1,212 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~127
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~41k

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 jiankang1991/nsfc-benzi-audit at commit 9a6010b, republished under its MIT licence (© jiankang1991). 1,212 words, ~2,462 tokens.

Download SKILL.mdSave it as .claude/skills/nsfc-benzi-audit/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.
name
nsfc-benzi-audit
description
Use for applicant-facing diagnosis or re-audit of a Chinese NSFC (国自然) application draft — 本子把脉、本子体检、帮我看国自然本子、申请书修改建议、标书逻辑诊断、青年/面上/地区基金申请书修改、对照已中本子、科学问题凝练、代表作支撑、选题撞题核查 or 申请代码检查. Accepts PDF/DOCX/Markdown/text and checks title, abstract, rationale, key scientific questions, research contents, innovation, feasibility, research basis and cross-section consistency, calibrated to the application year and form. Does not write applications from scratch or provide formal expert-review opinions.
license
MIT; see LICENSE

NSFC Benzi Audit

Produce applicant-facing diagnosis and revision advice grounded in the supplied draft. Expose substantive logic breaks, weak evidence and high-impact fixes. Do not fabricate literature, results, project histories, budgets or official requirements.

This workflow gives applicant revision advice. If the user requests formal communication review, identify that separate scope and use a suitable review skill only if available. No companion skill is required for draft-internal diagnosis.

Workflow

  1. Select the source and establish the review scope.

    • Prioritize the source and revision explicitly identified by the user. Separate target drafts, funded examples, old reports, templates and notes. Never select a draft merely because it is the largest Markdown file or named full.md/output.md.
    • Reuse extracted text only after matching its title, revision and contents to the selected original. Record source path/version and extraction provenance. If multiple plausible drafts cannot be distinguished, ask which one to use.
    • For PDF/DOCX, use available extraction/OCR tools and preserve headings and tables. If extraction is unavailable, state the limitation and work on readable supplied material; do not invent a tool or require a named companion skill.
    • Inspect original figures when judging visual logic or evidence, including preliminary results. Converted mermaid/OCR is not authoritative. Missing extraction is a material gap, not proof that the applicant omitted content.
    • Record application year, exact project category (including 青年 A/B/C where known), form version/source, funding mode (包干制/预算制/待确认), research attribute, application code and source completeness. Keep historical-example years separate from the target year.
    • Use questions, goals and methods as analytical dimensions wherever they occur. Require separate headings only when the applicable form requires them. If year or form is unknown, continue content diagnosis and mark rule applicability unresolved.
    • For a quick pass, focus on title, abstract, scientific questions, contents, innovation and basis. For full diagnosis, cover all supplied sections. A 专项 request (one chapter, one question) stays within that scope. Do not report absent attachments or omitted excerpts as confirmed defects in the original application.
    • For long or multi-file drafts, keep section/page locators and a running list of candidate findings with their locations while reading; before closing, revisit only unresolved candidates and report any source ranges you could not read.
  2. Load the relevant references.

    • Always read references/benzi-logic.md for logic diagnosis, writing advice and the signal → countercheck → grading table used for every finding.
    • Read references/current-rules.md before judging form, year/category compliance, research attributes, application codes, budgets, ethics or integrity requirements. It contains a dated 2026 baseline; verify rules for the target year and stage.
    • Read references/audit-surfaces.md for full diagnosis, figures, validation, annual plans, outcomes, budgets, literature or form checks.
    • Read references/question-distillation.md for question-source and distillation quality, or claims of 原创/独辟蹊径/瓶颈/交叉/跨域类比. Its strong forms apply when the draft actually makes that claim; they are not mandatory headings for every draft.
    • Read references/representative-works.md when the draft lists representative works or relies on publications. Prefer supplied PDFs, then available DOI/publisher/preprint lookup tools. A literature/citation lookup skill is an optional integration if installed. Distinguish bibliographic verification, abstract access and full-method verification; mark remaining evidence 未核实.
    • Read references/kd-lookup.md for topic collision, code calibration, output comparisons or applicant-requested self-overlap checks. The applicant runs portal queries; never automate login or captcha. Record module, query, year fields, date, error/zero-hit status and counts before making coverage claims.
    • Read references/exemplar-learning.md for funded/successful examples or improvement from sample applications. Use matched contexts, anonymized patterns and transferability limits; do not copy facts or distinctive wording into the target.
    • Read references/information-communication.md for information science, communications, networks, applied AI, security, quantum communication or related information engineering.
    • Read references/geospatial-remote-sensing.md for remote sensing, GIS, SAR/InSAR, optical/hyperspectral imagery, DEM/terrain, point clouds, spatial databases/graphs, trajectories, video GIS or city 3D models.
    • Read references/medical-biomedical.md for medicine, cohorts/specimens, disease mechanisms, cell/animal/organoid models, biomarkers, interventions, ethics or biosafety.
    • Use assets/report-template.md as an adaptable report shape unless the user requests another format.
  3. Build the logic and evidence maps.

    • Extract object/scenario, problem/goal, method/path, innovation, validation and expected significance; track them across title, abstract, rationale, contents, objectives, questions, route and basis.
    • Include the actual research attribute and any historical scientific-question statement when relevant, without mixing their form versions.
    • Build a many-to-many question–content–objective–validation map. Report uncovered questions or tasks with no explained scientific role, not unequal item counts. Supporting methods and validation tasks can share a question.
    • Distinguish the source of a question (literature, theory, observation, own work, demand) from the applicant's capacity to study it. Assess personal contribution, available resources and preliminary evidence in field-appropriate forms; no universal first-author SCI or pre-experiment threshold.
  4. Recheck prior findings when a prior report/list is supplied in files or chat.

    • First match it to the same application. Check every earlier 必改 item against both the new text and the applicable evidence/rule, then diagnose the current draft normally. Keep old IDs; give new issues unused IDs and cross-reference merged or split ones.
    • Use 已解决 / 部分落实 / 仍存在 / 改动无效 / 原意见撤销或不再适用 / 材料不足无法判断. Explain withdrawals, changed scope and incomplete evidence. Do not silently drop old items or preserve an incorrect finding merely because an earlier report said it.
  5. Diagnose by impact and give concrete actions.

    • Assess novelty, route, applicant contribution and resources. These are diagnosis dimensions, not fixed scoring weights or funding predictions.
    • Use the reference flags actively: they encode what reviewers repeatedly penalize (title/abstract drift, rationale not converging, contents written as purposes, questions that are tasks, hollow 首次/填补空白, decorative modifiers, silent topic switches, unquantified bottlenecks, uncashed analogies). Treat each hit as a candidate, run the countercheck in benzi-logic.md, then grade it 必改 / 待核实 / 建议改 / 可润色.
    • 必改: unanswered key questions, unsupported core innovation, broken coverage, infeasible critical steps, title/abstract promises the body never delivers, or verified material rule violations. 建议改: section-level craft or evidence weaknesses a reviewer is likely to notice. 可润色: wording and presentation preferences. Item counts, heading style and figure counts alone never reach 必改.
    • Give each root issue one stable ID and one full explanation; section notes reference the ID. For each finding cite the location/short phrase, explain its consequence and give the smallest actionable fix. Separate verified official requirements, logic/evidence risks and presentation suggestions. Do not pad findings; a draft can have no 必改 item.
    • Use fact-conditional revision skeletons with placeholders, not invented results or ready-made application claims. Label proposed expressions for applicant verification.
  6. Write the report and preserve its evidence trail.

    • Default filename: 本子诊断报告.md next to the selected draft; otherwise answer in chat. Before replacing an existing report, preserve it under a unique dated/revision filename and record which prior report was compared.
    • Include scope, overall assessment, one-page logic map, the prioritized finding list, prior-item recheck when applicable, and rewrite skeletons for 必改 items. For full diagnosis add a compact correspondence table (gap rows only) and one-line statuses for surfaces actually involved. The finding list carries all explanation; every other section is a one-line verdict, and each ID appears at most once outside the list. Per-chapter notes only when the user asks for them. If the user asks for a short answer (one paragraph, one chapter, a chat message), use that length; review depth and report length are separate choices.
    • Populate optional sections only when relevant. Record 已核查 / 部分核查 / 未核查 / 不适用 per surface, with evidence scope, sources and dates. Generate limitations from actual work rather than copying blanket disclaimers.
    • Write in simplified Chinese unless asked otherwise. Keep advice applicant-facing, quote only short supporting phrases, and separate 必改 from 可润色.

© jiankang1991, 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 13 other files (references, assets) in nsfc-benzi-audit of jiankang1991/nsfc-benzi-audit.

  • SKILL.md
  • LICENSE
  • agents/openai.yaml
  • assets/report-template.md
  • references/audit-surfaces.md
  • references/benzi-logic.md
  • references/current-rules.md
  • references/exemplar-learning.md
  • references/geospatial-remote-sensing.md
  • references/information-communication.md
  • references/kd-lookup.md
  • references/medical-biomedical.md
  • references/question-distillation.md
  • references/representative-works.md

Open the folder on GitHubat commit 9a6010b

Compare with similar skills

NSFC Application Audit 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.

NSFC Application Audit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
NSFC Application Audit this skilljiankang1991/nsfc-benzi-audit108—~2.5kAutomated safety check: PassMIT
Scientific Venue Templatesdavila7/claude-code-templates33k9 repos~5.1kAutomated safety check: NotesMIT
Academic HumanizerAIScientists-Dev/academic-humanizer1.9k1 repos~4.2kAutomated safety check: PassMIT
NSFC Grant Rationale Writerhuangwb8/ChineseResearchLaTeX2.9k—~945Automated safety check: PassMIT
NSFC Abstract Writerhuangwb8/ChineseResearchLaTeX2.9k1 repos~1.3kAutomated safety check: PassMIT
NSFC Research Significance WriterHuiyuLi-2000/Chinese-Grant-Writer-Skills4391 repos~790Automated safety check: PassMIT

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  • Academic Humanizer

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  • NSFC Grant Rationale Writer

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  • NSFC Abstract Writer

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Questions about NSFC Application Audit

What does NSFC Application Audit do?

Diagnoses a draft Chinese NSFC grant application for the applicant, pointing out logic breaks, weak evidence and high-impact fixes, calibrated to the application year and form. The agent accepts PDF, DOCX, Markdown or plain text and checks the title, abstract, rationale, key scientific questions, research contents, innovation, feasibility, research basis and consistency across sections. It starts by choosing the right source: the draft you name rather than the largest file, with funded examples, old reports and templates kept apart, and extracted text matched to the original.

When should I use NSFC Application Audit?

NSFC Application Audit fits situations like: getting a logic and evidence check on an NSFC application draft before submission; re-auditing a revised draft after changing the scientific question; comparing a draft's structure against a funded example.

How do I install NSFC Application Audit in Claude Code?

Run `npx skills add jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-audit -a claude-code`. Or copy the skill folder (nsfc-benzi-audit in jiankang1991/nsfc-benzi-audit) into .claude/skills/nsfc-benzi-audit in your project. Claude Code loads it when a task matches its description.

How do I install NSFC Application Audit in Codex?

Run `npx skills add jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-audit -a codex`. Or copy the skill folder (nsfc-benzi-audit in jiankang1991/nsfc-benzi-audit) into .agents/skills/nsfc-benzi-audit in your project. Codex loads it when a task matches its description.

Can I use NSFC Application Audit 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 jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-audit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nsfc-benzi-audit, .gemini/skills/nsfc-benzi-audit, .github/skills/nsfc-benzi-audit and .opencode/skills/nsfc-benzi-audit in your project.

What does NSFC Application Audit need to run?

SKILL.md names no scripts, command-line tools or credentials: NSFC Application Audit is instructions for the agent only. Our summary lists: PDF or DOCX text extraction or OCR tools, when the draft is not plain text.

Does NSFC Application Audit 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 NSFC Application Audit 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 NSFC Application Audit use?

NSFC Application Audit is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does NSFC Application Audit use?

About 2.5k tokens (SKILL.md is roughly 9.8k 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 39k tokens, read only when the agent opens those files.

What are the alternatives to NSFC Application Audit?

Skills that share tags, products or a category with NSFC Application Audit: Scientific Venue Templates (davila7/claude-code-templates, 33k stars), Academic Humanizer (AIScientists-Dev/academic-humanizer, 1.9k stars), NSFC Grant Rationale Writer (huangwb8/ChineseResearchLaTeX, 2.9k stars) and NSFC Abstract Writer (huangwb8/ChineseResearchLaTeX, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains NSFC Application Audit?

jiankang1991 (a GitHub user) maintains it in jiankang1991/nsfc-benzi-audit, which has 108 GitHub stars. The repository was last updated on October 8, 2026.

Source: jiankang1991/nsfc-benzi-audit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.