Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/richfrem/agent-plugins-skillsnpx agentmods add skills/richfrem/agent-plugins-skills/exploration-optimizerWrote 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/richfrem/agent-plugins-skills/exploration-optimizer)<a href="https://agentmods.dev/skills/richfrem/agent-plugins-skills/exploration-optimizer"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/exploration-optimizer/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/richfrem/agent-plugins-skills/exploration-optimizer"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/exploration-optimizer.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 | $0.00041 | $0.00420 |
| Opus 5.5 | $0.00016 | $0.00168 |
| Sonnet 5.5 | $0.00008 | $0.00084 |
| Haiku 4.5 | $0.00004 | $0.00042 |
Grade A, and why
exploration-optimizer 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 17d 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.
What it actually says
Exploration Optimizer (exploration-optimizer)
Evaluates and optimizes exploration-cycle skills and prompts using disciplined, baseline-first iteration loops.
Contents
Constraints
- One-hypothesis discipline: Change exactly one variable per iteration loop.
- Programmatic baselines: Acceptance requires automated benchmark score improvement over baseline.
- Fail-safe revert: Automatically discard regressions; retain only verified improvements.
Quick start
# Execute optimization loop on target skill
python ./scripts/execute.py \
--target plugins/exploration-cycle-plugin/skills/<skill>/SKILL.md \
--eval-script ./scripts/eval_runner.py \
--goal "Improve routing precision" \
--iterations 3
Workflow
- Configuration: Confirm target skill, evaluation benchmark script, and iteration budget.
- Baseline Run: Establish baseline score using deterministic evaluation fixtures.
- Mutation: Mutate one hypothesis at a time in isolated worktree.
- Scoring: Re-evaluate against the baseline. Keep wins, discard regressions.
- Ledger Declaration: Conclude with Source Transparency Declaration and iteration ledger.
Verification
# Verify evaluation fixtures run cleanly
pytest plugins/exploration-cycle-plugin/tests/
References
- acceptance-criteria.md — Acceptance criteria for exploration optimization loops.
- dispatch-strategies.md — Model dispatching and evaluation strategies.
What ships with it
9 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.
- evals/evals.json 875 B
- evals/results.tsv 60 B
- references/acceptance-criteria.md 64 B
- references/architecture.md 35 B
- references/cheapest_models.json 40 B
- references/cheapest_models.md 38 B
- references/dispatch-strategies.md 42 B
- references/exploration-output-standards.md 51 B
- scripts/execute.py 49 B runs code
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.
- 17d ago Changed · -33 lines 55acdf6bb90c
- 1mo ago First seen · 89 lines · 41 tokens per session scan A 2a651de8dcb8
exploration-optimizer is a skill published in the GitHub repository richfrem/agent-plugins-skills (7 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 420 once invoked, about $0.0002 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 2026-09-03.
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