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 evanyan22/loopengine --skill composio-large-outputsgit clone --depth 1 https://github.com/evanyan22/loopengineWrote 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/evanyan22/loopengine/composio-large-outputs)<a href="https://agentmods.dev/skills/evanyan22/loopengine/composio-large-outputs"><img src="https://agentmods.dev/badge/skills/evanyan22/loopengine/composio-large-outputs/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/evanyan22/loopengine/composio-large-outputs"><img src="https://agentmods.dev/badge/skills/evanyan22/loopengine/composio-large-outputs.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 | $0.00032 | $0.00211 |
| Opus 5.5 | $0.00013 | $0.00084 |
| Sonnet 5.5 | $0.00006 | $0.00042 |
| Haiku 4.5 | $0.00003 | $0.00021 |
Grade A, and why
composio-large-outputs 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 2mo 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
Gateway tools with a large result
Some gateway tools (Composio-sourced ones in particular) return a small pointer object instead of their real output when the actual result is too large to return inline:
{
"successful": true,
"storedInFile": true,
"tokenCount": 10234,
"outputFilePath": "/tmp/.../SOME_TOOL_OUTPUT_xxxxx.json"
}
When you see storedInFile: true in a tool result, the real data is
not in that object — it's in the file at outputFilePath. Call
system_read_file with that exact path to retrieve the actual content
before answering. Don't guess at an answer, summarize from the pointer
alone, or claim you don't have the data — read the file first.
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.
- 2mo ago First seen · 26 lines · 32 tokens per session scan A 5ba423ec3a95
composio-large-outputs is a skill published in the GitHub repository evanyan22/loopengine (2 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 211 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 2026-08-31.
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