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-gpt-skill-conversion-plangit 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-gpt-skill-conversion-plan)<a href="https://agentmods.dev/skills/okhp3/skillz/okhp3-gpt-skill-conversion-plan"><img src="https://agentmods.dev/badge/skills/okhp3/skillz/okhp3-gpt-skill-conversion-plan/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-gpt-skill-conversion-plan"><img src="https://agentmods.dev/badge/skills/okhp3/skillz/okhp3-gpt-skill-conversion-plan.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 | $0.00077 | $0.01368 |
| Opus 5 | $0.00039 | $0.00684 |
| Sonnet 5 | $0.00015 | $0.00274 |
| Haiku 4.5 | $0.00008 | $0.00137 |
Grade A, and why
okhp3-gpt-skill-conversion-plan 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 10d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
okhp3-gpt-skill-conversion-plan
OverKill Hill P³ · overkillhill.com · github.com/OKHP3
Convert a configured GPT into a durable, runtime-portable skill plan without
pretending that GPT configuration and Agent Skill instructions are equivalent.
This skill plans and audits the conversion; okhp3-skill-foundry authors and
benchmarks the final SKILL.md.
Scope
| In scope | Out of scope |
|---|---|
| Asset inventory, capability mapping, boundary design, portability analysis, semantic-loss tracking, migration sequencing, and Foundry handoff | Exporting private platform data, bypassing permissions, writing production integrations, or claiming feature parity without verification |
Conversion method
- Collect the source package. Inventory GPT name and purpose, instructions, knowledge files, actions/apps, starters, examples, eval prompts, user feedback, platform assumptions, version history, and any prompt-chain stages with their outputs. Mark each item
available,partial,missing, orunverifiedand label its claim class. - Map semantics, not wording. For each source behavior record its skill equivalent: trigger description, imperative procedure, reference, script, output contract, safety rule, or unresolved platform dependency. Convert a useful chain stage into a named procedure with inputs, observable exit criteria, and a recovery path. Preserve intent while removing UI-only language. Treat a claimed behavior as unproven until an example, preview result, or evaluation demonstrates it.
- Separate portable from platform-bound behavior. Keep reasoning patterns, schemas, rubrics, and public references in the skill. Isolate Builder toggles, ChatGPT-only UI, proprietary connectors, credentials, and undocumented model behavior as adapters or explicit exclusions.
- Detect semantic loss. Identify capabilities that cannot transfer cleanly: retrieval ranking, hidden system behavior, tool auth, connector permissions, conversation memory, model-specific formatting, and publishing controls. For each, state impact and a mitigation or acceptance test.
- Design the skill boundary. Define trigger phrases, in-scope and out-of-scope work, required inputs, outputs, escalation rules, references, scripts, assets, and version ownership. Avoid cloning an entire GPT when a smaller composable skill is more reliable. Record how the source hierarchy, tool policy, and failure handling will survive the move.
- Create a migration backlog. Order work as
preserve,rewrite,externalize,replace,verify, ordrop. Assign acceptance criteria and dependencies. Never carry secrets or private data into a public skill. - Plan Foundry validation. Propose exactly three distinct eval cases with four evidence-anchored expectations each. Include one semantic-preservation case, one platform-bound loss or adapter case, and one boundary or safety case when applicable. The Foundry should later run with-skill and without-skill comparisons, grade evidence, compute the delta, and iterate.
- Issue a disposition:
ready_for_foundry,needs_source_artifacts,partial_port,not_a_skill, orblocked_by_permissions. Explain what must happen next.
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.
- 10d ago First seen · 84 lines · 77 tokens per session scan A 0467eae26572
okhp3-gpt-skill-conversion-plan is a skill published in the GitHub repository OKHP3/skillz (3 stars, last pushed yesterday), licensed MIT. It adds 77 tokens to every session and 1,368 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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