claude-code-my-workflow is a forkable setup for using Claude Code to produce and review academic papers, slides, data analyses, and replication packages. Researchers use its agents, skills, rules, hooks, and quality checks to coordinate these tasks and verify their results. The catalogue entries define the reusable workflow components for Claude Code.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add pedrohcgs/claude-code-my-workflow --skill submission-disclosuresgit clone --depth 1 https://github.com/pedrohcgs/claude-code-my-workflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pedrohcgs/claude-code-my-workflow/submission-disclosures)<a href="https://agentmods.dev/skills/pedrohcgs/claude-code-my-workflow/submission-disclosures"><img src="https://agentmods.dev/badge/skills/pedrohcgs/claude-code-my-workflow/submission-disclosures/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pedrohcgs/claude-code-my-workflow/submission-disclosures"><img src="https://agentmods.dev/badge/skills/pedrohcgs/claude-code-my-workflow/submission-disclosures.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 65 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 66 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 69 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00111 | $0.01633 |
| Opus 5 | $0.00056 | $0.00816 |
| Sonnet 5 | $0.00022 | $0.00327 |
| Haiku 4.5 | $0.00011 | $0.00163 |
Grade A, and why
submission-disclosures scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/submission-disclosures — The Submission-Time Disclosure Block
Draft the four statements journals now require (or strongly expect) at submission, in one pass: AI-use disclosure, CRediT contributor roles, conflict-of-interest, and data availability. Journals tightened AI-use policies through 2025–2026; an undisclosed-AI finding at a top journal is now a research-integrity problem, not a formatting one — so the statement should be drafted deliberately, not improvised in the submission portal at midnight.
This skill is about the author's disclosures TO the journal. It is unrelated to /disclosure-check, which screens restricted-data outputs for statistical-disclosure risk (small cells, PII). Same word, different worlds.
When to use
- Preparing a submission or resubmission package and the portal asks for AI-use / COI / data-availability statements.
- A revise-and-resubmit at a journal that adopted an AI policy since the original submission.
- A coauthor asks "do we need to say we used Claude/Copilot/ChatGPT on this?"
Phases
Phase 1 — Resolve the journal's actual policy
- If a journal short-name is given, read its profile in
journal-profiles.md(top-5 econ + AEA-imprint policy notes + poli-sci top-3). - Verify the current policy on the journal's own site (
WebSearch/WebFetch: " artificial intelligence policy authors", the journal's submission guidelines page). Policies moved fast in 2025–2026; a cached or remembered policy is not good enough for a submission. Record the URL and retrieval date in the output. - If no explicit AI policy exists, default to the strictest common denominator (disclose tools, scope of use, and human responsibility) — over-disclosure is free; under-disclosure is not.
Phase 2 — Inventory what was actually used
Interview briefly (or infer from the repo when evident — e.g. quality_reports/, session logs, a CLAUDE.md):
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 77 lines · 111 tokens per session scan A 7021c02bb2bf
submission-disclosures is a skill published in the GitHub repository pedrohcgs/claude-code-my-workflow (1,570 stars, last pushed 16d ago), licensed MIT. It adds 111 tokens to every session and 1,633 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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