Agent skill

Radiology Response

by huang-sir1 in huang-sir1/radiology-skills

Adjudicate reviews, draft point-by-point responses and verify closure; not initial prereview.

Custom licenceAuto-check passed

Install Radiology Response

skills CLI
$ npx skills add huang-sir1/radiology-skills --skill radiology-response -a claude-code

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

GitHub CLI
$ gh skill install huang-sir1/radiology-skills radiology-response --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/huang-sir1/radiology-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/radiology-skills/skills/radiology-response .claude/skills/radiology-response && 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
radiology-response
GitHub stars
1.9k
Token cost
~4.6k tokens
SKILL.md length
1,933 words
Files
25 (incl. scripts, references)
Skills in repo
39
Repo updated
First seen
Licence
Custom licence

At a glance

Adjudicate reviews, draft point-by-point responses and verify closure; not initial prereview.

  • Works in 12 steps: Lock the evidence boundary — inventory… → Intake — parse manuscript metadata,… → Classify and adjudicate each item… → …
  • SKILL.md covers Core stance, When to use, When to open extra files and Workflow, plus 3 more sections
  • Runs PowerShell and Python scripts from its folder

What it does

Radiology Response is an agent skill from huang-sir1/radiology-skills. Adjudicate reviews, draft point-by-point responses and verify closure; not initial prereview.

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 27 other files, including scripts and reference files (for example `README.md`, `agents/openai.yaml` and `references/action-mapping.md`).

Example prompts

  • “/radiology-response”

Requirements

  • Python 3
  • PowerShell

Workflow steps

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

  1. Lock the evidence boundary — inventory the decision letter, reviewer reports, original and
  2. Intake — parse manuscript metadata, decision type, deadline/required files, and editor
  3. Classify and adjudicate each item (action-mapping.md): request class, separately sourced
  4. Map to action, evidence and location — state what changes, the method or operation, evidence
  5. Open the revision-letter writing chain and draft each response only from verified facts using
  6. Write the editor summary last — synthesize only completed material changes, changed claim
  7. For final response packages, open response-audit-gate.md and
  8. Audit independently in two passes — bind the audit to an artifact manifest with final
  9. Audit completeness, traceability, factuality, claim-strength conservation, tone, cross-review
  10. Output the requested letter or plan plus the commitment ledger, verification report and
  11. Generate the response receipt — copy
  12. Assemble only after closure — READY_FOR_SUBMISSION_ASSEMBLY means the response commitments

What it can do on your machine

Read from SKILL.md and the folder at commit aaa0fe6. 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

    Ships 4 files in scripts/ (PowerShell and Python, from the files we listed), which the agent can run.

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

  • Network

    Links to these hosts (documentation or services it may open):

    • nature.com

    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

Radiology Response loads about 4.6k tokens when it runs, and up to ~68k if it reads all its reference files. Until then it costs about 28 tokens; SKILL.md has 1,933 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~28
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~68k

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); the scripts in this folder are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 1,933 words (~4,566 tokens).

“Treat the response letter as an editor-facing verification document: every reviewer concern gets an ID, a classification, a concrete action, and a traceable manuscript location.”

— opening of SKILL.md by huang-sir1, Custom licence
name
radiology-response

Read the full SKILL.md on GitHub

Files

SKILL.md and 24 other files (scripts, references) in radiology-skills/skills/radiology-response of huang-sir1/radiology-skills.

  • SKILL.md
  • README.md
  • agents/openai.yaml
  • references/action-mapping.md
  • references/imaging-mechanism-reviewer-playbook.md
  • references/imaging-reviewer-playbook.md
  • references/mechanism-reviewer-playbook.md
  • references/prereview-response-state-crosswalk.md
  • references/radiogenomics-state-crosswalk.md
  • references/reject-decision-tree.md
  • references/response-audit-gate.md
  • references/revision-letter-writing-chain.md
  • references/transparent-peer-review-response-map-2024-2026.tsv
  • references/transparent-peer-review-response-patterns-2024-2026.md
  • scripts/audit_response_evidence_map.ps1
  • scripts/test_response_package_receipt.py
  • scripts/validate_response_package_receipt.py
  • scripts/validate_response_skill.ps1
  • … and 7 more

Open the folder on GitHubat commit aaa0fe6

Compare with similar skills

Radiology Response 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.

Radiology Response compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Radiology Response this skillhuang-sir1/radiology-skills1.9k—~4.6kAutomated safety check: PassCustom licence
Responsive Unitsthedaviddias/Front-End-Checklist74k—~472Automated safety check: PassMIT
Responsive Designwshobson/agents40k2 repos~498Automated safety check: PassMIT
Nature Reviewer ResponseYuan1z0825/nature-skills47k—~1.5kAutomated safety check: PassApache-2.0
Responsive Imagesthedaviddias/Front-End-Checklist74k—~403Automated safety check: PassMIT
Performing Ransomware Responsemukul975/Anthropic-Cybersecurity-Skills34k—~2.9kAutomated safety check: PassApache-2.0

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Questions about Radiology Response

What does Radiology Response do?

Adjudicate reviews, draft point-by-point responses and verify closure; not initial prereview. Radiology Response is an agent skill from huang-sir1/radiology-skills. Adjudicate reviews, draft point-by-point responses and verify closure; not initial prereview.

How do I install Radiology Response in Claude Code?

Run `npx skills add huang-sir1/radiology-skills --skill radiology-response -a claude-code`. Or copy the skill folder (radiology-skills/skills/radiology-response in huang-sir1/radiology-skills) into .claude/skills/radiology-response in your project. Claude Code loads it when a task matches its description.

How do I install Radiology Response in Codex?

Run `npx skills add huang-sir1/radiology-skills --skill radiology-response -a codex`. Or copy the skill folder (radiology-skills/skills/radiology-response in huang-sir1/radiology-skills) into .agents/skills/radiology-response in your project. Codex loads it when a task matches its description.

Can I use Radiology Response 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 huang-sir1/radiology-skills --skill radiology-response -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/radiology-response, .gemini/skills/radiology-response, .github/skills/radiology-response and .opencode/skills/radiology-response in your project.

What does Radiology Response need to run?

Going by SKILL.md and its folder, Radiology Response needs PowerShell and Python for the scripts in its folder. Our summary lists: Python 3; PowerShell.

Does Radiology Response access the network?

SKILL.md names 1 domain. As links in the text: nature.com. This is read from the text; nothing was executed.

Is Radiology Response 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Radiology Response use?

Radiology Response has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Radiology Response use?

About 4.6k tokens (SKILL.md is roughly 18k 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 63k tokens, read only when the agent opens those files.

What are the alternatives to Radiology Response?

Skills that share tags, products or a category with Radiology Response: Responsive Units (thedaviddias/Front-End-Checklist, 74k stars), Responsive Design (wshobson/agents, 40k stars), Nature Reviewer Response (Yuan1z0825/nature-skills, 47k stars) and Responsive Images (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Radiology Response?

huang-sir1 (a GitHub user) maintains it in huang-sir1/radiology-skills, which has 1,923 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on September 21, 2026.

Source: huang-sir1/radiology-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.