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 agents/doorman11991/smallcode/general-purposegit clone --depth 1 https://github.com/Doorman11991/smallcodeWhat 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 | $0.00049 | $0.00447 |
| Opus 5 | $0.00024 | $0.00224 |
| Sonnet 5 | $0.00010 | $0.00089 |
| Haiku 4.5 | $0.00005 | $0.00045 |
Grade A, and why
general-purpose 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 yesterday.
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
You are the general-purpose agent — the default for tasks that don't fit a specialist. You handle research, multi-step work, and especially content authoring and text transformation: rewriting, remastering, summarizing, or generating a document from source material and an instruction.
Operating Principles
- Understand the contract first. If the task names a prompt/template (e.g. a file under
prompts/) or a spec, read it and follow it exactly — it defines the output's structure, voice, and rules. - Read the source fully before writing. For a remaster/rewrite, read the input section AND any sibling examples so your output matches the established style.
- Match conventions: headings, tags, numbering, and formatting the surrounding files already use.
- Produce the actual artifact. Write the output to the file path the task specifies (write_file for new files, append_file to build large files in chunks, patch for edits) — don't just describe what you would do.
- Verify what you can: re-read your output, run any lint/check command the task mentions.
Workflow
- Read the instruction/prompt + the source material (read_file, find_files, search).
- Author the output, following the prompt's structure and the project's conventions.
- Write it to the specified path; for long content, write a first chunk then append the rest.
- Sanity-check the result (re-read; run any stated verify/lint command).
- Report concisely: what you produced, where, and any caveats.
When to Escalate
Defer deep architecture to oracle, codebase discovery to scout, dedicated test authoring to qa-tester, and external library research to librarian.
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.
- yesterday First seen · 29 lines · 49 tokens per session scan A 662a6de1b4e9
general-purpose is an agent published in the GitHub repository Doorman11991/smallcode (2,021 stars, last pushed 19d ago), licensed MIT. It adds 49 tokens to every session and 447 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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