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 drpwchen/textbook-to-note --skill figure-remapgit clone --depth 1 https://github.com/drpwchen/textbook-to-noteWrote 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/drpwchen/textbook-to-note/figure-remap)<a href="https://agentmods.dev/skills/drpwchen/textbook-to-note/figure-remap"><img src="https://agentmods.dev/badge/skills/drpwchen/textbook-to-note/figure-remap/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/drpwchen/textbook-to-note/figure-remap"><img src="https://agentmods.dev/badge/skills/drpwchen/textbook-to-note/figure-remap.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Prompt Injection · line 207 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 381 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00126 | $0.06449 |
| Opus 5.5 | $0.00050 | $0.02580 |
| Sonnet 5.5 | $0.00025 | $0.01290 |
| Haiku 4.5 | $0.00013 | $0.00645 |
Grade A, and why
figure-remap 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 1mo 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 — 515 lines — stays where its author put it; the contents beside it link to each section on GitHub.
figure-remap — deterministic document-grounding system
This skill calls scripts in your clone of the textbook-to-note repo. At install time, replace
{REPO}below with the absolute path of the clone.
Architecture (read this before implementation details)
figure-remap is a multi-backend deterministic document-grounding system, not a "crop utility." The system has six explicit layers:
┌─ Contract ──────────────────────────────────────────┐
│ figure_remap.extract() → {status, match_quality, │
│ hard_fail, file, fig_id, reason} │
├─ Policy ─────────────────────────────────────────────┤
│ strict = deterministic + ambiguity-intolerant │
│ L1 / L2 / L3 hard-fail hierarchy │
├─ Junk pre-gate ─────────────────────────────────────┤
│ pregate.verdict() on a QC-passed crop: │
│ chapter-banner geometry / blank → kill, no retry │
├─ Backend selection ─────────────────────────────────┤
│ Capability-based: _select_backend() │
│ "geometric" | "caption_anchor" | [future] │
├─ Backends ──────────────────────────────────────────┤
│ geometric_match_bbox() — born-digital rasters │
│ caption_anchor_bbox() — scanned / hybrid scans │
│ [future] layout-aware / table-aware │
├─ Analysis & cache ──────────────────────────────────┤
│ PageDerived (per-page, sha1-keyed, policy-versioned)│
│ _render_cache/<sha1>_pg<N>_<dpi>dpi.png │
├─ Debug artifacts ───────────────────────────────────┤
│ <out>.fail.json on every scanned-mode hard_fail │
└─────────────────────────────────────────────────────┘
Future backends plug in at the Backend layer with their own capability check and a function returning bbox + ambiguity flags — nothing above changes.
==Architectural freeze rule==: do not add per-book heuristics or
if scanned/elif born-digital branches into the gate function. New behavior
goes into a new backend plus a new capability check in _select_backend.
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.
- 1mo ago First seen · 515 lines · 0 tokens per session scan A 0536e22a2e7d
figure-remap is a skill published in the GitHub repository drpwchen/textbook-to-note (107 stars, last pushed 2mo ago), licensed MIT. It adds 126 tokens to every session and 6,449 once invoked, about $0.0005 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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