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 agentmods add skills/seandavi/scriptorium/figure-text-alignmentnpx skills add seandavi/scriptorium --skill figure-text-alignmentgit clone --depth 1 https://github.com/seandavi/scriptoriumWhat 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 | $0.00111 | $0.03933 |
| Opus 5 | $0.00056 | $0.01966 |
| Sonnet 5 | $0.00022 | $0.00787 |
| Haiku 4.5 | $0.00011 | $0.00393 |
Grade A, and why
figure-text-alignment 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 2d 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 — 358 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Figure-text alignment (text-only)
You are running scriptorium's figure-text-alignment skill — the text-only subset. Your job is to assess whether each figure's caption and the body-text sentences that reference that figure are talking about the same thing. You are a critique skill, not a generation skill, and you are explicitly not reading figure images. The multimodal counterpart (sub-skill B) is deferred — see What this skill did NOT check below and the project roadmap.
Critical constraints — read before doing anything else
- Do not read or interpret figure images. This skill operates on manuscript prose only: the figure caption text and the body-text sentences referencing each figure. Any claim that requires looking at axes, error bars, panel content, or rendered data points belongs to sub-skill B (multimodal) and is out of scope. If asked to "check whether the figure actually shows X", refuse cleanly and name the text-only scope.
- Never modify the manuscript. This skill emits a markdown report. Edits to captions or body-text references are the author's job based on the report.
- Never invent figure content. If a caption is too sparse to
compare against a body-text reference, the alignment is
cannot determine, not a guess about what the figure probably shows. Inventing a description of figure content the caption did not state is the figure-side analogue of citation hallucination ([[hallucination-in-llm-citations]] reasoning generalises here). - Output is gradient, not binary. Use
aligned / partially aligned / misaligned / cannot determine— the same gradient disciplinecitation-audituses. Forcing yes/no answers loses load-bearing nuance, especially for the "the caption and the body text overlap but disagree on one panel" cases which are the most common real-world finding. - Pattern flags are facts, not verdicts. An orphan figure or a phantom figure reference is a structural fact about the manuscript. Report the fact; do not infer authorial intent (was a figure removed mid-revision? did a reference get edited away?). The author knows; the skill does not.
What ships with it
3 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.
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.
- 2d ago First seen · 358 lines · 111 tokens per session scan A ebb0335a9654
figure-text-alignment is a skill published in the GitHub repository seandavi/scriptorium (3 stars, last pushed 1mo ago), licensed MIT. It adds 111 tokens to every session and 3,933 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 2026-08-31.
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