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 yha9806/academic-writing-toolkit --skill auditgit clone --depth 1 https://github.com/yha9806/academic-writing-toolkitWrote 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/yha9806/academic-writing-toolkit/audit)<a href="https://agentmods.dev/skills/yha9806/academic-writing-toolkit/audit"><img src="https://agentmods.dev/badge/skills/yha9806/academic-writing-toolkit/audit/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/yha9806/academic-writing-toolkit/audit"><img src="https://agentmods.dev/badge/skills/yha9806/academic-writing-toolkit/audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00040 | $0.04855 |
| Opus 5.5 | $0.00016 | $0.01942 |
| Sonnet 5.5 | $0.00008 | $0.00971 |
| Haiku 4.5 | $0.00004 | $0.00485 |
Grade A, and why
audit 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 10d 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 — 362 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/audit — Thesis Consistency Audit Skill
Running Python helpers
Choose the interpreter before running the examples. For a globally installed
copy, use the private runtime recorded by its installer. In a checkout or linked
workspace, use AWT_PYTHON when set, otherwise the toolkit's .venv (follow the
skill directory link back to the toolkit): Scripts/python.exe on Windows,
bin/python on macOS/Linux. Without that environment, check that python
(Windows) or python3 (macOS/Linux) actually runs and has the helper's dependencies.
Replace the example's python3 with that executable. In PowerShell, prefix a
quoted executable with &; keep commands on one line and quote file paths.
A manuscript registered with the writing loop
Run loop coverage <workspace> --run first (experimental/writing-loop/bin/loop). It
derives every check's inputs from the workspace (the tracked draft files at HEAD,
the bibliography, the ledgers, the target venue's corpus) instead of the thesis
defaults below, runs the ones the latest edits made due, and lists the checks
that cannot run on this manuscript and why. Its table covers the script checks
only: categories A, B and C below are read by the model, leave no run record, and
are listed under the table as such. Report any check it shows as not current,
missing a prerequisite, not applicable or failed, and never report a check it did
not run as clean.
Purpose
Scan all thesis chapters for internal data consistency issues: contradictory numbers, inconsistent terminology, broken cross-references, and arithmetic errors. This is a pre-submission quality check.
Trigger Words
This skill activates on: audit, consistency check, check numbers, /audit.
Workflow
-
Scan all chapter files in the
chapters/directory using Glob. Read each file to extract quantitative claims, terminology, and cross-references. -
Check the following categories:
A. Numerical consistency — read by the model, not checked by a script, except for what audit H binds. The three bullets below are what to look for; nothing verifies that you looked.
- The same statistic (e.g., accuracy, sample size, p-value) cited in multiple chapters must have the same value.
- Percentages in a distribution must sum to 100% (with tolerance of +/-1% for rounding).
- Counts (e.g., "42 models") must match between chapters.
What ships with it
18 files 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.
- scripts/audit-citation-fidelity.mjs 14 KB runs code
- scripts/audit-claim-ledger.py 31 KB runs code
- scripts/audit-claim-positioning.py 15 KB runs code
- scripts/audit-cross-refs.py 7.4 KB runs code
- scripts/audit-float-reviews.py 57 KB runs code
- scripts/audit-front-matter.py 25 KB runs code
- scripts/audit-generated-copies.py 25 KB runs code
- scripts/audit-method-ledger.py 28 KB runs code
- scripts/audit-number-ledger.py 19 KB runs code
- scripts/audit-prose-fingerprint.py 37 KB runs code
- scripts/audit-prose-structure.py 11 KB runs code
- scripts/audit-sentence-changes.py 65 KB runs code
- scripts/build-venue-baseline.py 13 KB runs code
- scripts/citations.mjs 1.5 KB runs code
- scripts/pdf-pages.mjs 530 B runs code
- scripts/prose-view.py 6.2 KB runs code
- scripts/quote-fidelity.mjs 1.9 KB runs code
- scripts/venue-topic-fit.py 13 KB runs code
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.
- 10d ago Changed · +1 lines 65976521ddc5
- 25d ago Changed · +20 lines 319376e9e44c
- 1mo ago Changed · +80 lines · +18 tokens per session 61d594099064
- 1mo ago Changed · +103 lines eeb0a0d3684c
- 1mo ago Changed · +11 lines 0ebfbdb94eb3
- 1mo ago Changed · +9 lines 12e2ec5f0d94
- 1mo ago Changed · +47 lines · -2 tokens per session 5dd61dbc9bf6
- 1mo ago First seen · 91 lines · 24 tokens per session scan A c9b276cd2bea
audit is a skill published in the GitHub repository yha9806/academic-writing-toolkit (49 stars, last pushed 11d ago), licensed MIT. It adds 40 tokens to every session and 4,855 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 2026-08-30.
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