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 mhawthorne/gza --skill gza-explore-summarizegit clone --depth 1 https://github.com/mhawthorne/gzaWrote 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/mhawthorne/gza/gza-explore-summarize)<a href="https://agentmods.dev/skills/mhawthorne/gza/gza-explore-summarize"><img src="https://agentmods.dev/badge/skills/mhawthorne/gza/gza-explore-summarize/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/mhawthorne/gza/gza-explore-summarize"><img src="https://agentmods.dev/badge/skills/mhawthorne/gza/gza-explore-summarize.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 | $0.00025 | $0.00937 |
| Opus 5 | $0.00013 | $0.00468 |
| Sonnet 5 | $0.00005 | $0.00187 |
| Haiku 4.5 | $0.00003 | $0.00094 |
Grade A, and why
gza-explore-summarize 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 9d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gza Explore Summarize
Summarize a completed explore task and turn its output into concrete next-step guidance. Use this when an explore task produced useful markdown or notes, but the user wants a faster handoff into planning, implementation, or a narrower follow-up exploration.
Inputs
- Required: full prefixed explore task ID (for example,
gza-1234) - Optional: context about what decision the user is trying to make next
If the user did not provide a full prefixed task ID, ask for it before proceeding.
Use the full prefixed task ID for all gza commands.
Goal
Produce a concise operator-facing synthesis:
- what the explore task found
- what matters most
- what remains uncertain
- what the best next steps are
This skill is not a raw inspection dump. Prefer synthesis and recommended actions over repeating the whole report.
Process
Step 1: Inspect the task
Run:
uv run gza show <TASK_ID>
uv run gza log <TASK_ID>
Use the output to verify:
- task exists
- task type is
explore - current status
- report or output content
- any execution/log context that changes how confident the findings are
If the task is not found or is not an explore task, stop and explain the mismatch.
Step 2: Read the exploration output
Use the report content from gza show or the report file it references.
Extract:
- main findings
- evidence or examples that support those findings
- recommendations already present in the report
- unresolved unknowns, risks, or missing context
If the output is thin, ambiguous, or clearly incomplete, use AskUserQuestion to clarify what decision the user is trying to make from this research.
Step 3: Synthesize what matters
Summarize the exploration in a compact, decision-oriented way.
Focus on:
- 3 to 7 findings at most
- the implications of those findings
- any disagreements, tradeoffs, or uncertainty that still affect the next step
Do not simply restate the report section by section.
Step 4: Recommend next actions
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.
- 9d ago First seen · 135 lines · 25 tokens per session scan A 5b8827bfb7cb
gza-explore-summarize is a skill published in the GitHub repository mhawthorne/gza (12 stars, last pushed yesterday), licensed MIT. It adds 25 tokens to every session and 937 once invoked, about $0.0001 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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