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 agentmods add skills/dysfunc/ai-plugins-cc/gemini-promptingnpx skills add dysfunc/ai-plugins-cc --skill gemini-promptinggit clone --depth 1 https://github.com/dysfunc/ai-plugins-ccWrote 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/dysfunc/ai-plugins-cc/gemini-prompting)<a href="https://agentmods.dev/skills/dysfunc/ai-plugins-cc/gemini-prompting"><img src="https://agentmods.dev/badge/skills/dysfunc/ai-plugins-cc/gemini-prompting.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.00774 |
| Opus 5 | $0.00014 | $0.00387 |
| Sonnet 5 | $0.00006 | $0.00155 |
| Haiku 4.5 | $0.00003 | $0.00077 |
Grade A, and why
gemini-prompting 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 5d 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
Gemini Prompting
Use this skill when gemini:gemini-rescue needs to ask Gemini for help via the task runtime.
Prompt Gemini like an analyst, not a collaborator with tool access. The plugin runs Gemini headless via gemini -p, so it cannot read files, run commands, or browse the working tree on its own. Everything Gemini sees has to be in the prompt text.
Core rules:
- Prefer one clear task per Gemini run. Split unrelated asks into separate runs.
- Tell Gemini what done looks like. Do not assume it will infer the desired end state.
- Keep prompts compact and block-structured with XML tags so the contract has stable shape.
- Inline any relevant code, log output, or file excerpts directly in the prompt — Gemini cannot fetch them.
- Add explicit grounding rules for any task where unsupported guesses would hurt quality (review, diagnosis, postmortem analysis).
- For follow-up requests, the plugin prepends the prior per-job transcript automatically; you only need to send the delta instruction.
Default prompt recipe:
<task>: the concrete job and the relevant repository or failure context (inlined).<structured_output_contract>or<compact_output_contract>: exact shape, ordering, and brevity requirements.<default_follow_through_policy>: what Gemini should do by default instead of asking routine questions.<grounding_rules>: required for review, research, or anything that could drift into unsupported claims.
When to add blocks:
- Diagnosis or planning: add
<completeness_contract>and an<observable_evidence>block listing what you've inlined. - Review or adversarial review: prefer the built-in
/gemini:reviewand/gemini:adversarial-reviewcommands — those carry the review contract and JSON schema. Only fall back totaskwhen the review needs a non-standard target or shape. - Research or recommendation tasks: add
<research_mode>and<citation_rules>(cite the inlined evidence by line reference, not URL).
Working rules:
- Prefer explicit prompt contracts over vague nudges.
- Use stable XML tag names so the structure is recognizable across runs.
- Do not raise reasoning effort first. Tighten the prompt and grounding rules before escalating.
- Ask Gemini for brief, outcome-based progress updates only when the task is long-running.
- Keep claims anchored to inlined evidence. If something is a hypothesis, say so.
- For long-running follow-ups, lean on
--resume-lastso the prior transcript is reused; the plugin truncates oldest turns when the transcript exceeds the cap.
Prompt assembly checklist:
- Define the exact task and scope in
<task>. - Inline the evidence Gemini needs to answer — file excerpts, log slices, error messages, schemas.
- Choose the smallest output contract that still makes the answer easy to use.
- Decide whether Gemini should keep going by default or stop for missing high-risk details.
- Add grounding and verification tags only where the task needs them.
- Remove redundant instructions before sending the prompt.
Common antipatterns:
- Asking Gemini to "look at file X" — it cannot. Inline X (or a relevant slice) in the prompt instead.
- Asking Gemini to "run the tests and report" — it cannot. Run them yourself, inline the output, then ask Gemini to analyze.
- Restating the full prompt on every
--resume-lastturn — the prior transcript is already prepended. - Mixing several unrelated questions in one prompt — split them into separate
taskruns.
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.
- 5d ago First seen · 53 lines · 28 tokens per session scan A ce42002d0f2e
gemini-prompting is a skill published in the GitHub repository dysfunc/ai-plugins-cc (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 28 tokens to every session and 774 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 2026-08-31.
Other skills, from other repositories
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grok-prompting
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