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 redongreen/uSpec --skill extract-structuregit clone --depth 1 https://github.com/redongreen/uSpecWrote 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/redongreen/uspec/extract-structure)<a href="https://agentmods.dev/skills/redongreen/uspec/extract-structure"><img src="https://agentmods.dev/badge/skills/redongreen/uspec/extract-structure/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/redongreen/uspec/extract-structure"><img src="https://agentmods.dev/badge/skills/redongreen/uspec/extract-structure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Rogue Agent · line 132 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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 | $0.00078 | $0.12761 |
| Opus 5.5 | $0.00031 | $0.05104 |
| Sonnet 5.5 | $0.00016 | $0.02552 |
| Haiku 4.5 | $0.00008 | $0.01276 |
Grade A, and why
extract-structure 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 — 603 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extract Structure Data
Interpretation-only companion to create-structure. This skill does not extract data from Figma. It reads {cachePath}/{componentSlug}-_base.json (produced by the uSpec Extract Figma plugin), applies the same reasoning layer as create-structure, and writes the normalized StructureSpecData JSON to disk for the create-component-md orchestrator to consume.
Quality contract: every reasoning step (section planning, ownership resolution, override promotion, design-intent notes, anomaly detection) mirrors create-structure/SKILL.md. Any improvement to structure-extraction quality must be made in both places.
Batch-mode contract. This skill MUST NOT call AskQuestion, prompt for confirmation, or pause for user input. When a value cannot be resolved from _base.json (and a Step 3-delta doesn't recover it), emit a row with provenance: "not-measured" and values: ["—", …] instead of asking. No mid-interpretation clarifications.
Invocation Contract
The orchestrator calls this skill with these inputs (already resolved — do NOT re-parse URLs or re-read uspecs.config.json):
componentSlug— filename-safe slugcachePath— cache directory, typically.uspec-cache/{componentSlug}/optionalContext— free-form string from the user (may be"none")mcpProvider—figma-consoleorfigma-mcp(only used if a Step 3-delta escape hatch fires)deltaAvailable— boolean derived from_base.json._meta.fileKey+nodeId. Plugin exports normally make thistrue; a separately-passedfigmaLinkis not required.apiDictionaryPath— absolute or workspace-relative path to{cachePath}/{componentSlug}-api-dictionary.json. Optional. When present, this file is the canonical vocabulary for axis/value/sub-component/state naming (see Step 2.5). When absent, the skill continues with_dictionaryUnavailable: truein its output envelope and the renderer treats the produced cache as lower-confidence.evidencePath— optional. Path to{cachePath}/{componentSlug}-evidence-structure.jsonfrom CLI prepare. When present and hash-valid, usedataas the Step 3 working evidence set.
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 Changed · +3 lines d4ce5706790c
- 1mo ago First seen · 600 lines · 78 tokens per session scan A 70944a19159d
extract-structure is a skill published in the GitHub repository redongreen/uSpec (248 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 12,761 once invoked, about $0.0003 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.
Other skills, from other repositories
accessibility-per-component
Audit one design system component's accessibility against WCAG 2.2 AA: keyboard, screen reader, contrast, focus, ARIA, target size. Trigger: a11y audit, is this accessible, WCAG check, screen reader support, keyboard navigation check. Not for page- or product-wide audits.
figma-variable-audit
Audit Figma variable collections: tier mapping, naming, alias chains, modes, orphans; can fix in place with Figma Console MCP. Triggers: audit my Figma variables, review variable collections, Figma variable health. For token files in code use token-audit.
metadata-schema-generator
Generate per-component JSON metadata files (.ai/metadata/) from source: props, behaviour, composition, a11y contract, prohibited prop combinations. Triggers: component metadata schema, machine-readable component JSON, manifest for MCP/codegen. Prose for Figma: use ai-component-description.
theme-audit
Audit theme parity: tokens missing or unchanged per theme, component tokens bypassing semantics, contrast within each theme, resolver contexts, theme-switch regressions. Triggers: dark mode audit, theme coverage, brand variant parity. For general token structure use token-audit.
token-audit
Audit how design tokens are defined: tiers, naming, alias chains, raw values, orphans, DTCG readiness. Triggers: audit my tokens, token architecture review, token health check. Not for code consuming tokens (token-compliance), theme parity (theme-audit) or Figma variables (figma-variable-audit).
token-compliance
Find hardcoded colour, spacing and type values and wrong-tier token references in consuming code. Trigger: find hardcoded values, any hex in the code, are we using tokens correctly, token compliance. Do NOT use for token definitions — token-audit; token file format — schema-validator.