Mindloom needs to be fully working as an MCP server for LLM agents. This means that there…
failedTask 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
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Finalized
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Merged to
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Runtime health
runner is missing go but the proof matrix requires Go tests
Last error
–
Run state
Status.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
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"success": true,
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"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
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verify.result.json
{
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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