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/conorbronsdon/agent-context-osnpx agentmods add skills/conorbronsdon/agent-context-os/mine-gemini-workflowsWrote 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/conorbronsdon/agent-context-os/mine-gemini-workflows)<a href="https://agentmods.dev/skills/conorbronsdon/agent-context-os/mine-gemini-workflows"><img src="https://agentmods.dev/badge/skills/conorbronsdon/agent-context-os/mine-gemini-workflows.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00738 |
| Opus 5 | $0.00017 | $0.00369 |
| Sonnet 5 | $0.00007 | $0.00148 |
| Haiku 4.5 | $0.00003 | $0.00074 |
Grade A, and why
mine-gemini-workflows 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 8d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mine Gemini workflows
Use session evidence to find workflows worth porting. This is workflow archaeology, not a bulk conversation export.
Non-negotiable privacy boundaries
- Require one explicitly selected Gemini project/session directory. Never crawl the entire home directory by default.
- Run the metadata-only pass first.
- Do not extract or summarize private thoughts, reasoning fields, tool arguments, secrets, or complete transcripts.
- Do not commit
.context-os/migrations/or raw Gemini recordings. - Ask before any
--include-content,--include-summaries, or--include-pathspass and explain exactly which selected sessions will be read. - A repeated pattern is a candidate, not authorization to create or install a skill.
Procedure
1. Select evidence
Ask the user for the relevant Gemini project/session directory and optional date boundary. If they do not know the directory, help them locate candidate directories using names and modification dates only; do not read session bodies during discovery.
2. Create a metadata-only inventory
Run:
python3 scripts/mine-gemini-workflows.py \
<selected-session-directory> \
--output .context-os/migrations/<timestamp>/gemini-inventory.json
Add --since YYYY-MM-DD when the user supplied a date boundary. The default report includes tool names, validation status, file basenames, and session identifiers. It excludes message text, free-form workflow summaries, tool arguments, and full paths.
3. Rank candidates
Prioritize candidates that:
- occur with positive validation in at least two sessions,
- have successful validation evidence,
- use a stable tool sequence,
- solve a task the user expects to repeat.
Do not promote one-off activity or a repeated failure. Present the ranked candidates and evidence counts, then ask the user which ones to inspect.
4. Inspect only selected sessions
If metadata is insufficient, name the exact selected session IDs and ask permission to rerun with repeated --session-id <id> selectors plus only the required opt-in flag (--include-summaries, --include-paths, or --include-content). Content redaction is best-effort, not a guarantee; treat every opt-in report as sensitive. Thought/reasoning fields remain excluded. Review the output again before sharing or persisting it.
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.
- 8d ago First seen · 72 lines · 35 tokens per session scan A 572ae7f41760
mine-gemini-workflows is a skill published in the GitHub repository conorbronsdon/agent-context-os (23 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 738 once invoked, about $0.0002 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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