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 sendralt/agentic-awesome-skills --skill accint-solvegit clone --depth 1 https://github.com/sendralt/agentic-awesome-skillsWrote 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/sendralt/agentic-awesome-skills/accint-solve)<a href="https://agentmods.dev/skills/sendralt/agentic-awesome-skills/accint-solve"><img src="https://agentmods.dev/badge/skills/sendralt/agentic-awesome-skills/accint-solve/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/sendralt/agentic-awesome-skills/accint-solve"><img src="https://agentmods.dev/badge/skills/sendralt/agentic-awesome-skills/accint-solve.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 | $0.00031 | $0.00444 |
| Opus 5 | $0.00015 | $0.00222 |
| Sonnet 5 | $0.00006 | $0.00089 |
| Haiku 4.5 | $0.00003 | $0.00044 |
Grade A, and why
accint-solve 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 9d 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.
This is a copy
94% identical to accint-solve — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
solve
When to Use
Use this skill when you need route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.
Routing sugar over the two MCP verbs — no logic lives here.
- Call
acc_act(runtime="solve", input="<the goal>"). - If the result is final: surface the answer, the
commitmentid, and the cited[ids]. - If the result is a brain_frame: it is YOUR deliberation turn — the frame is typed
(which hole, what was retrieved, what is predicted). Reason over it, then submit via
acc_act(runtime="continue", input={"frame_id": ..., "submit_token": ..., "proposal_text": ...}). - End
proposal_textwithPREDICT: <0.00-1.00> <why>; acc strips that line before the owner sees it and uses it to calibrate the Work Model against later outcomes. - Never leave a received frame unresolved; never solo-derive outside the loop.
- Close the commitment honestly later with
acc_act(runtime="outcome", ...).
Limitations
- Use this skill only when the task clearly matches its upstream source and local project context.
- Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
- Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.
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.
- 9d ago First seen · 36 lines · 31 tokens per session scan A 792ef7e64416
accint-solve is a skill published in the GitHub repository sendralt/agentic-awesome-skills (1 stars, last pushed 2d ago), licensed MIT. It adds 31 tokens to every session and 444 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to accint-solve, differing in 8 lines, and is treated as a copy.
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