The tired-manager-with-git-diff problem.
Small task, run checks, inspect diff, pull it back on scope, repeat. AccInt turns that loop into a ledger the agent can operate against.
For agent builders coming from Reddit
The context window is not your project manager.
Claude Code, Codex, Cursor, and OpenCode can write real code. The hard part is keeping the work accountable: what is open, what changed, what passed, what failed, and what is allowed next.
Open promisesblocked, active, stale, and done are explicit states.
Evidence packets"Done" needs checks, receipts, and what was not tested.
Outcome creditOnly reality teaches the next run what to trust.
Install the local Work Model
Paste this into the agent you already use. It will run the installer and wire itself in.
Install AccInt for yourself - a local Work Model for agent work. I want it to track open promises, evidence, checks, outcomes, and what actually worked across my projects so Claude Code, Codex, Cursor, or OpenCode start with accountable work state instead of a context dump. Run the installer for my OS - macOS/Linux: curl -fsSL https://accint.xyz/install | sh; Windows PowerShell: irm https://accint.xyz/install.ps1 | iex - then run `acc hosts-sync` to wire yourself onto it, and tell me when `acc retrieve` works. It's local: no account, no API key, and it asks before anything leaves my machine.
Best for Claude Code, Codex, Cursor, OpenCode. One paste, then the agent runs the setup.
curl -fsSL https://accint.xyz/install | sh
Windows PowerShell:
irm https://accint.xyz/install.ps1 | iex
Why this is different
Your agent needs accountable work state, not a bigger pile of context.
Reddit threads about coding agents keep circling the same problem: the model can produce code, but the human still has to manage the work. AccInt makes that management layer explicit and local.
"Done" is a state transition.
The agent can propose completion. The Work Model waits for evidence: files changed, checks run, what was not tested, what could still break.
Worked once is not a universal rule.
Fixes only become trusted when reality confirms them in context. Stale or self-claimed lessons stay weak.
The flow
Agent work becomes a loop you can inspect.
Work Model looplocal / receipted / owner-gated
- promiseRecord the task state: open, blocked, stale, done, and the next concrete action.OPEN
- actRun the work through the agent you already use, with real commands and receipts.HELD
- proveAttach evidence: checks, files changed, owner approval, external reply, or a failed gate.EVIDENCE
- settleLet reality grade it. Passing tests and real outcomes count more than the agent's own confidence.CREDIT
- carryStart the next run ahead with the accountable state that actually earned trust.NEXT
No account, no API key, no cloud control plane.
One binary and one local substrate. External actions are held for your OK.
Keep Claude Code, Codex, Cursor, or OpenCode.
AccInt sits underneath the agents already doing your work.
Reddit community
Bring real agent-work friction, not generic AI hype.
We opened r/AccretedIntelligence as a public workbench for Work Models, work packets, open promises, evidence packets, approval gates, and outcome credit. The useful posts are concrete: root-cause packets, commitment boundaries, install friction, teardown notes, and operator workflows.
Template
Root-cause packet
For failures where the transcript looked fine but reality diverged.
Template
Commitment boundary
For deciding what can be automatic and what must stay gated.
Template
Failure report
When the agent says done but the evidence does not hold.
Template
Install friction
Useful for improving the first real human install path.
Template
Workflow teardown
Concrete operator friction beats abstract agent takes.
Join r/AccretedIntelligence
Post a root-cause packet
If your agent looked productive but increased your review load, that is exactly the kind of report that helps. Keep links out unless they are necessary evidence.