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 OKHP3/skillz --skill okhp3-custom-gpt-readinessgit clone --depth 1 https://github.com/OKHP3/skillzWrote 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/okhp3/skillz/okhp3-custom-gpt-readiness)<a href="https://agentmods.dev/skills/okhp3/skillz/okhp3-custom-gpt-readiness"><img src="https://agentmods.dev/badge/skills/okhp3/skillz/okhp3-custom-gpt-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/okhp3/skillz/okhp3-custom-gpt-readiness"><img src="https://agentmods.dev/badge/skills/okhp3/skillz/okhp3-custom-gpt-readiness.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 | $0.00078 | $0.01308 |
| Opus 5 | $0.00039 | $0.00654 |
| Sonnet 5 | $0.00016 | $0.00262 |
| Haiku 4.5 | $0.00008 | $0.00131 |
Grade A, and why
okhp3-custom-gpt-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 11d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
okhp3-custom-gpt-readiness
OverKill Hill P³ · overkillhill.com · github.com/OKHP3
Turn scattered GPT ideas and partial artifacts into a buildable, testable brief. This is an intake and gap-analysis skill, not the builder itself.
Scope
| In scope | Out of scope |
|---|---|
| Concept triage, evidence inventory, requirement elicitation, readiness scoring, and builder handoff | Writing production integrations, managing credentials, publishing a GPT, or claiming volatile platform limits |
Operating contract
- Inventory before asking. Inspect the supplied conversation, notes, files, prior prompts, prompt-chain stages, and existing GPT export. Record each artifact as
present,partial,missing, orconflicting; never ask for information already present. - Classify every claim. Quote or point to the source artifact for every
presentclaim. Label itverified_platform_fact,source_derived_practice,theory,preference,inferred, orunknown. A source assertion does not become a platform fact by being repeated. - Assess the eight readiness domains: job and audience, outcomes, boundaries, conversation contract, instruction behavior, knowledge/data, tools and permissions, and evaluation/governance.
- Identify blockers. A missing primary job, audience, safety boundary, allowed data source, or acceptance test is a build blocker. Do not declare a concept ready while a blocker remains unresolved.
- Ask only high-yield questions. Return the smallest question set that closes the largest blockers. Group questions by domain and explain why each answer matters.
- Score transparently. Score each domain 0 to 3:
0 missing,1 vague,2 usable with assumptions,3 explicit and evidenced. Report the total, percentage, blockers, assumptions, and confidence. A score is not a substitute for blocker review. - Choose a disposition:
ready_for_builder,ready_with_questions,needs_artifact_recovery,not_a_custom_gpt, orblocked_by_authority. Explain the decision. - Plan maturity from the start. For each acceptance test, state its evidence source, the failure it guards against, and how a future revision will be evaluated. For a multi-step build, produce an intake, contract, configuration, challenge, release, and recovery map. Each stage needs an input, observable exit gate, and recovery action. Treat untested claims as hypotheses, not release criteria.
- Produce a handoff. When the user is ready to continue, emit a builder-ready brief containing confirmed requirements, open questions, source evidence, non-goals, acceptance tests, safety constraints, and unresolved platform facts marked
verify.
What ships with it
2 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.
- 11d ago First seen · 80 lines · 78 tokens per session scan A 2958f965dccf
okhp3-custom-gpt-readiness is a skill published in the GitHub repository OKHP3/skillz (3 stars, last pushed today), licensed MIT. It adds 78 tokens to every session and 1,308 once invoked, about $0.0004 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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