dental-author-disclosures

dental-author-disclosures is a skill for Codex from Tuminha/dental-ai-skills. It costs 59 tokens per session (2,114 once invoked), scanned A, original, MIT.

A research workflow for recording the financial and professional relationships publicly disclosed by authors of a dental paper. It distinguishes documented relationships from claims that a relationship caused bias or misconduct.

In plain words
What is it for?
Use it to read a paper's full text, build a sourced relationship register, and explain how each disclosed relationship may matter to interpreting the work.
Why use it?
It helps readers assess possible relevance without treating a grant, job, patent, or affiliation as proof that the research is unreliable.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to read a paper's full text, build a sourced relationship register, and explain how each disclosed relationship may matter to interpreting the work.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tuminha/dental-ai-skills/dental-author-disclosures
Install

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.

Any agent
npx skills add Tuminha/dental-ai-skills --skill dental-author-disclosures
Clone the repo
git clone --depth 1 https://github.com/Tuminha/dental-ai-skills

Made for: Codex.

Wrote 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.

agentmods badge for dental-author-disclosures

README.md
[![agentmods](https://agentmods.dev/badge/skills/tuminha/dental-ai-skills/dental-author-disclosures/github.svg)](https://agentmods.dev/skills/tuminha/dental-ai-skills/dental-author-disclosures)
Your own site
<a href="https://agentmods.dev/skills/tuminha/dental-ai-skills/dental-author-disclosures"><img src="https://agentmods.dev/badge/skills/tuminha/dental-ai-skills/dental-author-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.

agentmods 80×15 button for dental-author-disclosures

Your own site · 80×15
<a href="https://agentmods.dev/skills/tuminha/dental-ai-skills/dental-author-disclosures"><img src="https://agentmods.dev/badge/skills/tuminha/dental-ai-skills/dental-author-disclosures.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,114 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00059 $0.02114
Opus 5.5 $0.00024 $0.00846
Sonnet 5.5 $0.00012 $0.00423
Haiku 4.5 $0.00006 $0.00211

Measured 29d ago against content hash 9e9453f38cfd, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

dental-author-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 29d 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.

dental-author-disclosures/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dental Author Disclosures

Skill protocol version: 2026.09.30 Methodology Review Date: 2026-09-30 (added step 0 on the reviewer's own relationships, "Sharing, sources and retention", the expanded source standard with the ICMJE 36-month window, and the register hand-off as a report section table; earlier the same day "How relationships inform appraisal" and "Full text first"; previous review 2026-09-27)

Scope

Document relationships, not a blacklist or a credibility score. A relationship can be relevant to interpretation without proving biased research. Never infer payment, commercial sponsorship, or misconduct from a name, conference appearance, membership, coauthorship, or missing search result. Do not automatically reduce a paper's score.

Full text first

The funding and disclosure statements are in the full text. An abstract rarely has them. When the runtime can run scripts, get the PDF with dental-paper-fetch before building the register. Never build the register from the abstract when a free full text exists. Otherwise ask the user for a PDF they may lawfully share. State in the search scope whether the full text, part of it or only the abstract was read. An author address that dental-paper-fetch prints is for a full-text request only and never enters the register.

Procedure

  1. State the reviewer's own relationships to the studied products and organisations before starting, for example "founder of a dental education site; no relationship with the manufacturer studied". Write "none" when there are none. The reviewer is the person the register is for: ask them when the statement is not known, and put it at the top of the register.
  2. Establish the paper: title, DOI, publication and study dates, manufacturer/product studied, author names, affiliations, and ORCID where available. Disambiguate each person using at least two matching details. Leave ambiguous identities unresolved.
  3. State retrieval capability and coverage. If browsing or full text is unavailable, extract from supplied documents only and provide a search plan. Never pretend a search was performed. An abstract rarely contains complete disclosure information.
  4. Read the article's funding and disclosure statements, supplements, protocol and registration first. Preserve the distinction between institution and individual.
  5. Search public primary sources: author/university disclosures, funder/grant records, company advisory or speaker pages, dated official meeting programmes, and patent records. Search every author, but report which were actually checked and where a bounded search stopped. Secondary reporting is a lead, not proof of a relationship.
  6. Record study-period evidence separately from current relationships. Use the journal's stated disclosure period. If the journal uses the ICMJE disclosure form, the window is the 36 months before submission for every item other than support for the submitted work, which has no time limit. If the period is unknown, state the searched dates without inventing a universal disclosure obligation. A newer relationship is not evidence that it existed during the study. A now-missing webpage does not prove it ended.
  7. Classify: employment; consultancy/advisory; speaking/honoraria; research funding; travel/material support; patents/equity; non-financial/professional affiliation; other/unclear. Paid status remains unknown unless the source establishes it. Professional societies and educational foundations are not automatically vendors.
  8. Compare each source with the paper's disclosure. Say "not found in the supplied disclosure" rather than "concealed". Explain the possible connection to the studied intervention, sponsor role, design, analysis or reporting; do not infer actual bias.
  9. Keep conflicting sources and identity uncertainties visible. Hand off methodological concerns to research-critic; body-of-evidence questions to clinical-evidence-reviewer.

Read the full file on GitHub · 146 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 29d ago First seen · 146 lines · 59 tokens per session scan A 9e9453f38cfd

Subscribe to this mod's changes

dental-author-disclosures is a skill published in the GitHub repository Tuminha/dental-ai-skills (7 stars, last pushed 7d ago), licensed MIT. It adds 59 tokens to every session and 2,114 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-01.

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