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 liza-mas/liza --skill check-liza-input-readinessgit clone --depth 1 https://github.com/liza-mas/lizaWrote 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/liza-mas/liza/check-liza-input-readiness)<a href="https://agentmods.dev/skills/liza-mas/liza/check-liza-input-readiness"><img src="https://agentmods.dev/badge/skills/liza-mas/liza/check-liza-input-readiness/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/liza-mas/liza/check-liza-input-readiness"><img src="https://agentmods.dev/badge/skills/liza-mas/liza/check-liza-input-readiness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00122 | $0.02610 |
| Opus 5 | $0.00061 | $0.01305 |
| Sonnet 5 | $0.00024 | $0.00522 |
| Haiku 4.5 | $0.00012 | $0.00261 |
Grade A, and why
check-§BRAND_NAME_LOWER§-input-readiness 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 4d 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 — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Objective
Assess whether a document gives §BRAND_NAME_TITLE§ agents enough signal to produce quality artifacts and code for the selected entry point.
Output a readiness report, not a rewrite. The report answers:
- Is the document ready for the requested entry point?
- If not, what would force agents to guess, block, or produce low-quality artifacts?
- Is another entry point a better fit?
- What exact questions or edits would make it ready?
Inputs
Require both:
- Document path: the source document to assess.
- Target entry point: one of
general-objective,functional-spec,detailed-spec, ortechnical-spec.
If either is missing, ask for it before assessing.
Treat detailed-spec as a legacy alias of functional-spec.
Protocol
1. Read
Read the full input document before judging it. For long Markdown documents, use heading navigation first, then read every relevant section.
If the document lives in a Git repository, run a read-only status check for the document path. Warn if it is untracked or uncommitted: worktrees are created from the configured integration branch, so uncommitted input may not be visible to agents.
Declare what you read in the report. If token limits prevent full reading, stop and report the partial scope instead of issuing a readiness verdict.
2. Classify Entry-Point Fit
Compare the document's altitude to the requested entry point:
| Entry point | Starts at | Document must already contain |
|---|---|---|
general-objective |
Epic planning | Product intent: why, users, scope, behavior, success, and product decisions. |
functional-spec / detailed-spec |
Architecture | Functional behavior already resolved enough for architects to define structure. |
technical-spec |
Code planning | Architecture and implementation boundaries already resolved enough for code planners. |
If the document is good but aimed at a different altitude, return Wrong entry point rather than Not ready.
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.
- 4d ago Changed · +25 lines 23657ce70056
- 12d ago First seen · 187 lines · 122 tokens per session scan A 53b7099c1d8d
check-§BRAND_NAME_LOWER§-input-readiness is a skill published in the GitHub repository liza-mas/liza (387 stars, last pushed yesterday), licensed Apache-2.0. It adds 122 tokens to every session and 2,610 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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