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Unstuck

Skill momentmaker/kaijutsu/skills/core/unstuck

Write your dev workflow once. Run it on any LLM. Open agent skills + multi-model swarm + a local findings store that learns which models you can trust.

Install
npx -y skills add momentmaker/kaijutsu --skill unstuck

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 3 stars3 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Guided problem articulation when you're stuck. Use when the user says "unstuck", "I'm stuck", "this isn't working", "help me think through this", "I keep going in circles", or invokes /unstuck. Helps break out of unproductive loops by forcing clarity before the next attempt.

SKILL.md

7.6 KB, as published. Nobody here has run it

Unstuck

Break out of unproductive loops. Articulate the problem, then either solve it through clarity or escalate systematically.

Step 0.5's iron-law framing + multi-component instrumentation pattern adapted from obra/superpowers/skills/systematic-debugging under MIT.

Step 0: Memory-first

Before asking the user anything, check project memory for prior similar problems:

  1. Read MEMORY.md index, scan descriptions for matches against the current symptom (error message, stack trace, behavior)
  2. For any matches, read the full memory entry
  3. If a strong match exists, present it: "We've hit something like this before: <prior root cause>. Is this the same problem? If yes, the prior fix was: <fix>."

If the user confirms it's the same problem, jump straight to Step 5 (Solution Capture) — the entry confirms the user already had the answer.

If no match or user says it's different, proceed to Step 0.5.

Memory format follows the project-memory schema — kebab-case slug + YAML frontmatter (name / description / type).

Step 0.5: Gather evidence

Iron law: no fix proposals without root-cause investigation first. Symptom-fixes mask underlying issues and create new bugs. This step is for the AGENT to do legwork BEFORE asking the human articulation questions — so Step 1's discussion is grounded in facts, not memory of facts.

  1. Read the actual error message in full.

    • Don't paraphrase. Copy the literal stack trace, exit code, log line.
    • Note line numbers, file paths, error codes — the message often contains the exact answer.
    • If the error was N invocations ago and you don't have it, ask the user to re-run with the failure reproduced.
  2. Check recent changes.

    • git log --oneline -10 on suspect files
    • git diff against last known good
    • New dependencies, config edits, env-var changes
    • The cause is usually in the most recent change, but the SYMPTOM may surface later.
  3. Verify reproducibility.

    • Does the failure happen every time, or intermittently?
    • Exact steps to reproduce. If intermittent → gather more data, do not guess.
    • If "I keep going in circles" was the trigger, the problem may be that the symptom is non-deterministic.
  4. Multi-component systems: instrument boundaries.

    • When the system has multiple components (CI → build → deploy, API → service → DB, swarm → cache → render):
      • Log what data ENTERS each component
      • Log what data EXITS each component
    • The bug is at the boundary where input ≠ expected. Find the boundary BEFORE proposing a fix.
  5. Surface the evidence to the user before Step 1.

    • Present what you found: "Error says X. Last change touched Y. Reproducer is Z."
    • Then ask the Step 1 articulation questions — they're now augmenting your evidence, not replacing it.

Skip this step ONLY when:

  • Step 0 found a memory match and the user confirmed it (jump straight to Step 5)
  • The user has already provided full evidence in their initial message

If you find yourself wanting to skip because "I'm pretty sure I know what it is" → that's the rationalization the iron law exists to block. Run the evidence-gathering anyway.

Walk-away timer

If unstuck has been invoked 2+ times in the same session on the same goal, escalate Step 4's Walk-Away level immediately. Repeated invocation = fresh-eyes problem, not articulation problem.

Step 1: Articulate

Ask these 4 questions one at a time. Do not skip any.

  1. "What are you trying to do?"

    • The goal — the outcome, not the implementation detail.
  2. "What did you expect to happen?"

    • The assumption being violated.
  3. "What actually happened?"

    • The concrete symptom: error message, wrong behavior, unexpected state. Be specific.
  4. "What have you tried so far?"

    • Each approach, briefly. This is the attempt log. Knowing what failed is as valuable as knowing what worked.

Step 2: Reflect

Read back the articulated problem as a structured summary:

## Problem Statement

**Goal:** {answer 1}
**Expected:** {answer 2}
**Actual:** {answer 3}

### Attempts
1. {attempt 1}
2. {attempt 2}
...

Then ask: "Does seeing this written out change anything? Often the answer becomes visible once the problem is articulated."

If the user sees the answer → skip to Step 5 (Solution Capture).

Step 3: Pivot

If still stuck, suggest 3 fundamentally different angles. Tailor to the actual problem, but the three categories are:

  1. Reverse direction — "You're debugging from {current direction}. Try from the other end."

    • Top-down → bottom-up (or vice versa)
    • Reading code → writing a test
    • Tracing forward → tracing backward from the symptom
  2. Isolate — "Can you reproduce this in the smallest possible case? Strip away everything except the broken behavior."

    • Create a minimal test case
    • Comment out everything unrelated
    • Hardcode inputs to eliminate variables
  3. Simplify — "Remove code until it works, then add back line by line until it breaks."

    • Binary search for the offending change
    • git stash and verify the problem exists on a clean state
    • Revert to last known good and re-apply changes one at a time

Ask which angle to try. Help execute that approach.

Step 4: Escalate

If pivoting didn't help, work through this ladder:

Level 1: Search

  • Search for the exact error message
  • Grep the codebase for similar patterns that work
  • Check if this is a known issue in the library/framework

Level 2: Read Source

  • Don't read docs — read the actual source code of the library or framework involved
  • Find the function that throws the error or produces the unexpected behavior
  • Understand what it actually does vs what you assumed

Level 2.5: Blunder hunt

  • Invoke blunder-hunt on the file or function suspected to be broken
  • Five passes with different lenses (data, error handling, integration, invariants, hostile input) often surface the cause that single-lens debugging missed
  • If blunder-hunt is not installed, run the equivalent manually: 5 passes of skeptic critique with deliberately different attention each pass

Level 3: Walk Away

  • Record the full problem state in your agent's persistent memory:
    • Goal, symptoms, all attempts, what was learned
    • File paths and line numbers involved
    • Any theories not yet tested
  • Tell the user: "Problem state saved. Come back with fresh eyes — it'll be here when you return."

Step 5: Solution Capture

After the problem is resolved (at any step), ask:

"What was the actual root cause?"

Then write a project-memory entry (per docs/project-memory.md):

---
name: <symptom-slug>
description: <symptom> -> <root cause>
type: project
source: unstuck
---

**Symptom:** <what happened>
**Root cause:** <what was actually wrong>
**Fix:** <what solved it>
**How to apply:** <when this knowledge is useful in the future>

Update MEMORY.md if the root cause is likely to recur. Future unstuck invocations will find this entry in Step 0 and short-circuit.

Update the project-level memory index if the root cause is likely to recur.

If the user declines to capture, that's fine — don't push.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.