CM
Codex Machine

Mindloom needs to be fully working as an MCP server for LLM agents. This means that there…

Mindloom needs to be fully working as an MCP server for LLM agents. This means that there…

failed
Task ID
task-20260410-125723-fde6
Worktree
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6
Task file
/home/hal9000/docker/cognisphere/data/environments/mindloom/mailbox/failed/00010-mindloom-needs-to-be-fully-working-as-an-mcp-server-for-llm-agents-this-means-that-there-task-20260410-125723-fde6.md
Runtime archive
Finalized
Merged to
Runtime health
runner is missing go but the proof matrix requires Go tests
Last error

Run state

Status.json
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RunState.json
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RuntimeHealth.json
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Task file

id: task-20260410-125723-fde6
status: failed
title: Mindloom needs to be fully working as an MCP server for LLM agents. This means that there…
workflow: hardened-delivery
priority: normal
created_at: 2026-04-10T12:57:23Z
updated_at: 2026-04-13T08:30:59Z
run_id: 20260413-083042-1d33
branch: machine/mindloom/task-20260410-125723-fde6
worktree: /home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6
status_file: /home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/Status.json

## Request
Mindloom needs to be fully working as an MCP server for LLM agents. This means that there is a server running that is fully compliant with the MCP protocol, where the LLM can read and store memory snippets. The MCP configuration needs to consist of a unique ID so that the coding agent and the memory can be attached.

Also make sure that the dashboard for mindloom is fully working again, showing all the memories, all the processes and their status, basically "what is happening in this brain" so that I can see what happens with all the stored memory.

## Acceptance Hints
- Working and fully featured UI/Dashboard to see what is happening behind the courtains
- Fully working MCP server, where memory can be read and stored.

## Human Notes
- none

## Agent Updates
- 2026-04-10T12:57:57Z Task claimed by environment runner.
- 2026-04-11T14:33:43Z Task claimed by environment runner.
- 2026-04-11T18:26:29Z Task claimed by environment runner.
- 2026-04-11T19:51:15Z Task claimed by environment runner.
- 2026-04-12T17:03:27Z Task claimed by environment runner.
- 2026-04-13T08:30:42Z Task claimed by environment runner.

## Agent Result
- none

Result files

resume_gate.result.json
{
  "node_id": "resume_gate",
  "command": "bash .machine/runtime/resume_gate.sh",
  "success": true,
  "exit_code": 0,
  "log_file": "/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/logs/resume_gate.log",
  "started_at": "2026-04-13T08:30:56Z",
  "completed_at": "2026-04-13T08:30:58Z"
}
triage.output.json
{"action":"proceed","summary":"The task can proceed with strong defaults. The request is broad but implementable without additional product decisions: use a stable unique MCP instance ID, ensure memory read/write compliance, and restore the dashboard to show memories, processes, and their statuses.","questions":[]}
triage.result.json
{
  "node_id": "triage",
  "agent": "triage",
  "model": "gpt-5.4-mini",
  "reasoning": "medium",
  "sandbox": "danger-full-access",
  "success": true,
  "exit_code": 0,
  "output_file": "/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/results/triage.output.json",
  "prompt_file": "/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/artifacts/triage/prompt.md",
  "log_file": "/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/logs/triage.log",
  "started_at": "2026-04-13T08:30:43Z",
  "completed_at": "2026-04-13T08:30:56Z",
  "schema": "question_gate.schema.json"
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verify.result.json
{
  "node_id": "verify",
  "command": "bash .machine/runtime/verify.sh",
  "success": false,
  "exit_code": 2,
  "log_file": "/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/logs/verify.log",
  "started_at": "2026-04-13T08:30:58Z",
  "completed_at": "2026-04-13T08:30:59Z"
}

Logs

resume_gate.log
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/logs/resume_gate.log
.machine/runtime/ResumeMode.json
RESUME_GATE_MODE=resume
existing task-owned candidate state detected; matrix and verification plan are valid, so resume from executable proof
triage.log
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/logs/triage.log
exec
/bin/bash -lc "pwd && printf '\\n--- Task ---\\n' && sed -n '1,220p' .machine/runtime/Task.md && printf '\\n--- Repo AGENTS ---\\n' && if [ -f AGENTS.md ]; then sed -n '1,260p' AGENTS.md; fi && printf '\\n--- Notes ---\\n' && if [ -f .machine/runtime/Notes.md ]; then sed -n '1,220p' .machine/runtime/Notes.md; fi" in /home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6
 succeeded in 0ms:
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6

--- Task ---
id: task-20260410-125723-fde6
status: active
title: Mindloom needs to be fully working as an MCP server for LLM agents. This means that there…
workflow: hardened-delivery
priority: normal
created_at: 2026-04-10T12:57:23Z
updated_at: 2026-04-13T08:30:42Z
run_id: 20260413-083042-1d33
branch: machine/mindloom/task-20260410-125723-fde6
worktree: /home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6
status_file: /home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/Status.json
current_node: triage
current_agent: triage

## Request
Mindloom needs to be fully working as an MCP server for LLM agents. This means that there is a server running that is fully compliant with the MCP protocol, where the LLM can read and store memory snippets. The MCP configuration needs to consist of a unique ID so that the coding agent and the memory can be attached.

Also make sure that the dashboard for mindloom is fully working again, showing all the memories, all the processes and their status, basically "what is happening in this brain" so that I can see what happens with all the stored memory.

## Acceptance Hints
- Working and fully featured UI/Dashboard to see what is happening behind the courtains
- Fully working MCP server, where memory can be read and stored.

## Human Notes
- none

## Agent Updates
- 2026-04-10T12:57:57Z Task claimed by environment runner.
- 2026-04-11T14:33:43Z Task claimed by environment runner.
- 2026-04-11T18:26:29Z Task claimed by environment runner.
- 2026-04-11T19:51:15Z Task claimed by environment runner.
- 2026-04-12T17:03:27Z Task claimed by environment runner.
- 2026-04-13T08:30:42Z Task claimed by environment runner.

## Agent Result
- none

--- Repo AGENTS ---
# AGENTS.md

## Operating contract

You are the software delivery system for this repository.

Your job is not to stop when the code looks plausible. Your job is to leave the repository in a state that can survive skeptical verification.

The human user is often on a phone. Minimize back-and-forth. Infer reasonable implementation choices unless a missing detail would materially change the product outcome.

## Model budget policy

Use expensive models only where they materially improve outcomes.

Preferred routing:
- specification, architecture, milestone planning: strongest available model
- implementation, refactors, test writing, repair passes: lower-cost implementation model
- acceptance and code review gates: strongest reviewer model in read-only mode
- documentation or framework spot checks: mini model or docs specialist

Avoid waste:
- do not spawn subagents unless they add clear value
- do not use a frontier model for routine code edits, mechanical fixes, or simple retries
- keep subagent fan-out small because every child session consumes additional tokens

## Clarification policy

Ask questions only when a wrong assumption would invalidate the deliverable.

Do not ask about:
- preferred frameworks
- preferred libraries
- coding style preferences
- implementation details the repo or task can reasonably imply

If the task is implementable with sensible defaults, choose them and proceed.

Ask at most 3 short clarification questions total, and only if truly necessary.

## Delivery workflow

For every non-trivial task, follow this sequence:

1. Read:
   - `workflow/IncomingTask.md`
   - `workflow/Prompt.md`
   - `workflow/Plan.md`
   - `workflow/Implement.md`
   - `workflow/Completion.md`
   - `workflow/Documentation.md`
   - `workflow/code_review.md`
2. Refresh `workflow/Prompt.md` so it is the clear specification.
3. Refresh `workflow/Plan.md` so it has milestone checkpoints, acceptance criteria, and validation commands.
4. Refresh `workflow/Implement.md` so it is a concrete runbook.
5. Refresh `workflow/Completion.md` so every requirement has an evidence slot.
6. Implement milestone by milestone using TDD whenever practical:
   - write or update tests first
   - make them fail for the right reason
   - implement the code
   - make the tests pass
7. After each milestone, run `./scripts/verify.sh`.
8. If verification fails, fix it before continuing.
9. Keep `workflow/Documentation.md` current while you work.
10. Keep `workflow/Completion.md` current with concrete evidence:
    - exact commands run
    - tests that passed
    - files changed
    - observable behavior

## Completion policy

Never treat prose as proof.

The work is not complete merely because:
- code was written
- a build succeeded once
- the implementation seems aligned with the prompt
- the model thinks the task is probably done

Treat `workflow/Completion.md` as an evidence ledger, not as a status boast.

Only mark an acceptance item as satisfied when there is concrete evidence for it.

The shell orchestrator is the final source of truth for completion. It decides success only after:
- `./scripts/verify.sh` passes
- the read-only acceptance gate passes
- the read-only review gate passes

## Planning rules

`workflow/Prompt.md` is the product specification.
`workflow/Plan.md` is the milestone plan.
`workflow/Implement.md` is the runbook.
`workflow/Completion.md` is the evidence ledger.
`workflow/Documentation.md` is the audit log.

Keep them aligned.

If you discover that the current plan is flawed, incomplete, or impossible:
- update `workflow/Plan.md`
- update `workflow/Implement.md` if the runbook must change
- record the reason in `workflow/Documentation.md`
- update `workflow/Completion.md` if the acceptance surface changed
- continue under the revised plan

Do not continue blindly under a broken plan.

## Scope control

Keep diffs scoped to the current task.
Do not perform unrelated refactors unless they are required to make the task work safely.
If you must widen scope, document why.

## Review behavior

Review like an owner, not a stylist.

Prioritize:
- correctness
- regressions
- missing tests
- security issues
- broken UX flows
- bad assumptions
- incomplete edge cases
- operational issues
- missing documentation for changed behavior

Do not rubber-stamp.

## Failure behavior

If you hit a real external blocker, stop and state it clearly.
A real blocker is something like:
- missing credentials
- a required service is unavailable
- upstream outage
- missing proprietary artifact
- impossible requirement conflict

In that case:
- explain the blocker succinctly
- record it in `workflow/Documentation.md`
- leave the repo in the cleanest useful state

--- Notes ---
# Notes

Optional operator notes.

codex
{"action":"proceed","summary":"The task can proceed with strong defaults. The request is broad but implementable without additional product decisions: use a stable unique MCP instance ID, ensure memory read/write compliance, and restore the dashboard to show memories, processes, and their statuses.","questions":[]}
tokens used
20,487
{"action":"proceed","summary":"The task can proceed with strong defaults. The request is broad but implementable without additional product decisions: use a stable unique MCP instance ID, ensure memory read/write compliance, and restore the dashboard to show memories, processes, and their statuses.","questions":[]}
verify.log
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/logs/verify.log
TEST_MATRIX_GUARD_OK
TEST_MATRIX_GUARD_OK
PLAN_GUARD_OK
VERIFY_PREFLIGHT_FAIL: runner is missing go but the proof matrix requires Go tests
VERIFY_PREFLIGHT_ARTIFACT: /home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/Preflight.json
Verification blocked. See .machine/runtime/Preflight.json for machine-owned blockers.

Previous attempts

20260412-170327-59bd
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260412-170327-59bd
20260411-195115-de0d
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260411-195115-de0d
20260411-182629-e95a
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260411-182629-e95a
20260411-143343-9f1f
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260411-143343-9f1f
20260411-093151-f578
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260411-093151-f578
20260411-082555-cafe
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260411-082555-cafe
20260410-195951-b54d
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260410-195951-b54d
20260410-131826-e8ff
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260410-131826-e8ff
20260410-131720-4aab
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260410-131720-4aab
20260410-125757-9fe9
/home/hal9000/docker/cognisphere/data/environments/mindloom/worktrees/task-20260410-125723-fde6/.machine/runtime/attempts/20260410-125757-9fe9