accint-solve
Helps your agent find solutions to a goal. It uses a memory system to think and decide the best path, useful for solving problems intelligently.
What it does
This tool helps the AI think through a problem using its memory and reasoning. It either gives you the final answer or asks for your input to decide the next step.
When to use it
- ✓When you want the AI to solve a complex problem.
- ✓When the AI needs to use what it has already learned to answer you.
- ✓When the AI needs your opinion to proceed.
Example of what to ask your AI
“Solve this problem: [describe the problem here]”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The AI uses its memory to try and solve your request. If it's unsure, it shows you its thoughts and asks for your input to decide how to move forward.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill accint-solveOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/accint-solve/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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", ...).
Example
User request:
Use @accint-solve for this task: Route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.
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.
FAQ
What is a 'scored-memory loop'?
It's how the AI accesses and uses its existing knowledge to tackle new problems.
What is a 'brain_frame'?
It's a summary of the AI's current thinking, showing what it understood and what it predicts next. It asks for your help to interpret it.
What does 'deliberate' mean?
It means to think carefully about something. In this context, the AI is asking you to think with it about the 'brain_frame'.
Details
Original description by the author
Route a goal through acc's scored-memory loop via acc_act(runtime="solve"); deliberate any returned brain_frame and submit via continue.
Popularity
- GitHub stars
- 48k
- Ranking position
- #2025
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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