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 gemini-cli-extensions/sre --skill data-ingestiongit clone --depth 1 https://github.com/gemini-cli-extensions/sreWrote 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/gemini-cli-extensions/sre/data-ingestion)<a href="https://agentmods.dev/skills/gemini-cli-extensions/sre/data-ingestion"><img src="https://agentmods.dev/badge/skills/gemini-cli-extensions/sre/data-ingestion/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/gemini-cli-extensions/sre/data-ingestion"><img src="https://agentmods.dev/badge/skills/gemini-cli-extensions/sre/data-ingestion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 30 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00017 | $0.00448 |
| Opus 5.5 | $0.00007 | $0.00179 |
| Sonnet 5.5 | $0.00003 | $0.00090 |
| Haiku 4.5 | $0.00002 | $0.00045 |
Grade A, and why
data-ingestion 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 1mo 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
Data Ingestion Skill
This skill is responsible for fetching and converting time-series data from different sources into a standardized JSON format for other skills to consume.
Inputs:
source_type: String indicating the data source (e.g., "csv", "cloud_monitoring").source_details: A dictionary or list containing the necessary information to access the data source.- For
source_type: "csv": A list of file paths.
- For
Output:
A JSON string in the standardized format (see README.md for details).
Workflow:
- Validate Inputs: Check if
source_typeandsource_detailsare provided. - Route to Parser: Based on
source_type:- If
source_typeis "csv":- Ensure
source_detailsis a list of file paths. - Create a list of temporary file names for intermediate JSON outputs (e.g.,
~/.gemini/tmp/user/parsed_0.json, ...). - Parse Each CSV: Iterate through the input file paths:
- Execute
python ./skills/data-ingestion/parse_csv.py <input_csv_path> > <temp_json_path>usingrun_shell_command(with venv activation). - Check for errors.
- Execute
- Merge JSONs: Execute
python ./skills/data-ingestion/merge_timeseries.py <temp_json_path_1> <temp_json_path_2> ...usingrun_shell_command(with venv activation). - Capture the stdout from
merge_timeseries.pyas the final result. - Clean up: Remove the temporary JSON files.
- Handle any errors during script executions.
- Ensure
- If
source_typeis not supported, return an error message.
- If
- Return JSON: Output the standardized JSON string.
What ships with it
3 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.
- 1mo ago First seen · 40 lines · 17 tokens per session scan A 203be260bb37
data-ingestion is a skill published in the GitHub repository gemini-cli-extensions/sre (84 stars, last pushed 7d ago), licensed Apache-2.0. It adds 17 tokens to every session and 448 once invoked, about $0.0001 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 2026-08-30.
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