Borrowing it
Nothing to install: this file belongs to Alexander-M-Dickerson/ai-asset-pricing. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Alexander-M-Dickerson/ai-asset-pricing/main/.claude/skills/check-consistency/SKILL.mdgit clone --depth 1 https://github.com/Alexander-M-Dickerson/ai-asset-pricingWrote 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/alexander-m-dickerson/ai-asset-pricing/check-consistency)<a href="https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/check-consistency"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/check-consistency/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/alexander-m-dickerson/ai-asset-pricing/check-consistency"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/check-consistency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00016 | $0.00801 |
| Opus 5 | $0.00008 | $0.00400 |
| Sonnet 5 | $0.00003 | $0.00160 |
| Haiku 4.5 | $0.00002 | $0.00080 |
Grade A, and why
check-consistency 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 13d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Check Consistency Skill
Fast, focused scan for cross-section inconsistencies in main.tex. Lighter than /full-paper-audit -- designed for iterative use during editing.
Examples
/check-consistency-- full scan of main.tex/check-consistency numbers-- only check quantitative claims/check-consistency terminology-- only check terminology consistency
Workflow
Step 1: Load Reference Values
Read guidance/paper-context.md to get canonical values (if it exists):
- Key quantitative results and their canonical magnitudes
- Sample description (date range, number of observations, variable counts)
- Any other numbers that appear in multiple sections
If no paper-context file exists, the skill still works by cross-referencing sections against each other (without a canonical reference).
Step 2: Quantitative Consistency
Grep main.tex for all quantitative claims and cross-reference:
- Percentages and basis points mentioning specific variables or factors
- Sample period mentions (start date, end date, number of periods)
- Counts (variables, observations, subsamples, etc.)
- Any number that appears in more than one section
Flag: mismatches between text claims and canonical values (if available), or between sections.
Step 3: Terminology Consistency
If guidance/paper-context.md defines a terminology table, grep across all sections for violations.
Also check for within-paper drift regardless of paper-context:
- Same concept called different names in different sections
- Inconsistent abbreviation introduction (defined in one section, used without definition in another)
- Check against
.claude/rules/banned-words.mdfor hard-banned terms
Step 4: Cross-Reference Integrity
- Extract all
\ref{...}and\eqref{...}targets - Extract all
\label{...}definitions - Flag any
\refor\eqrefthat points to a non-existent label - Flag any
\refused where\eqrefshould be (equation references) - Check that all tables and figures are cited at least once in the text
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.
- 13d ago First seen · 86 lines · 16 tokens per session scan A e8b8aada7d75
check-consistency is a skill published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 4mo ago), licensed MIT. It adds 16 tokens to every session and 801 once invoked, about $0.0001 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 2026-08-30.
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