Borrowing it
Nothing to install: this file belongs to DIGI-UW/OpenELIS-Global-2. 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/DIGI-UW/OpenELIS-Global-2/develop/.specify/oe/skills/overview/SKILL.mdgit clone --depth 1 https://github.com/DIGI-UW/OpenELIS-Global-2Wrote 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/digi-uw/openelis-global-2/overview)<a href="https://agentmods.dev/skills/digi-uw/openelis-global-2/overview"><img src="https://agentmods.dev/badge/skills/digi-uw/openelis-global-2/overview.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
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 →
- medium Excessive Agency · line 8 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 36 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00125 | $0.01073 |
| Opus 5 | $0.00063 | $0.00536 |
| Sonnet 5 | $0.00025 | $0.00215 |
| Haiku 4.5 | $0.00013 | $0.00107 |
Grade A, and why
overview 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 8d 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/speckit.overview Skill
Use this skill when:
- a feature's SpecKit artifacts (
spec.md+plan.md+research.md+tasks.md+ optionaldata-model.md+contracts/) are complete and you want a stakeholder-friendly interactive canvas of the content - preparing a spec PR for non-engineering review (designers, QA, product, lab admins) — the canvas surfaces the structure without forcing readers through 200KB of dense markdown
- demoing a feature's design to stakeholders external to the engineering team
- maintaining a "single pane of glass" overview that drills down into the underlying spec files
- onboarding a new engineer onto a feature — the canvas's Overview tab gives them the executive summary; the Spec Files tab lets them drill into any file's markdown rendered with proper headings, code blocks, tables
Primary Entrypoint
/speckit.overview <SPEC_DIR>— reads the spec markdown files, extracts canvas data intocanvas-data.json, assemblescanvas/overview.htmlfrom the template, and prints the deployed-on-merge URL.
If <SPEC_DIR> is omitted, the skill auto-detects from git branch --show-current (e.g., feat/ogc-285-spec-cleanup → specs/OGC-285-barcode-label-presets/).
Lifecycle
- Detect / accept spec dir —
specs/<feature>/. - Extract —
scripts/extract-spec-data.py <SPEC_DIR>reads spec.md / plan.md / research.md / tasks.md and writes<SPEC_DIR>/canvas/canvas-data.json. - Build —
scripts/build-canvas.py <SPEC_DIR>substitutes the JSON intotemplates/canvas.html.templateand writes<SPEC_DIR>/canvas/overview.html. - Verify — open the file locally to confirm rendering; the GitHub Pages workflow auto-deploys on push to main.
- Surface URL — print the deployed URL (
https://digi-uw.github.io/OpenELIS-Global-2/specs/<feature>/canvas/overview.html) so it can be attached to PR / Jira.
Core Non-Negotiables
- 2-level progressive disclosure only (tabs → expandable cards). No deeper nesting. See reference/canvas-ux-research.md for the Nielsen Norman Group guidance behind this.
- 5–7 KPI cards on the Overview tab (cognitive comfort zone per B2B Dashboard IA 2026 research).
- Strong information scent — every tab has a count badge; every expandable card has a status chip before expanding.
- Light + dark mode — default = system
prefers-color-scheme; user choice persists to localStorage. - Spec Files tab renders markdown inline via
marked+ DOMPurify CDN — readers don't have to leave the canvas to read the source. - Standardized data shape — see reference/data-extraction.md for the JSON schema.
- No personal-references content — the canvas should reflect what the spec contains, not litigate retrospectives. If the spec is professional, the canvas is professional.
What ships with it
7 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.
- 8d ago First seen · 61 lines · 125 tokens per session scan A d73fb7635089
overview is a skill published in the GitHub repository DIGI-UW/OpenELIS-Global-2 (251 stars, last pushed today), licensed MPL-2.0. It adds 125 tokens to every session and 1,073 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 2026-08-30.
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