think — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited think (Agent Skill) and scored it 96/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 1 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 1 flagged
The text {match} tells the agent to skip the normal "ask the user first" gate. Used adversarially it removes the human-in-the-loop check before destructive or sensitive actions, turning a normally-gated agent into a fire-and-forget executor.
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
A structured thinking skill that guides human-AI collaboration through Bloom's cognitive levels. The human leads evaluation and judgment (Levels 5-6), AI handles research, execution, and documentation (Levels 1-3), and both collaborate on analysis (Level 4).
Core principle: Always start at Level 5 (Evaluate). Never jump to building, drafting, or coding before the human has answered the evaluative questions.
Interaction model: Use the AskUserQuestion tool for ALL decision points. This makes the framework faster and more guided than free-form Q&A.
┌─────────────────────────────────────────┐
│ Level 6: Create HUMAN → AI │ Direction and vision
│ Level 5: Evaluate HUMAN → AI │ Judgment and decisions
│ Level 4: Analyze HUMAN ↔ AI │ Research and comparison
├─────────────────────────────────────────┤ ← TRUST BOUNDARY
│ Level 3: Apply AI → HUMAN │ Draft, build, produce
│ Level 2: Understand AI → HUMAN │ Explain in plain language
│ Level 1: Remember AI alone │ Save to Second Brain
└─────────────────────────────────────────┘L1-L3 sit below the trust boundary — output has an external referent (source post, document, runtime behavior) that can be verified. L4-L6 sit above it — ground truth is the human's judgment and values, which only the human holds. See the Auditability Principle section at the end of this file.
Full 6+3 questions + mandatory L4↔L5 spiral + Level 3 deliverable + save. Use for any decision, project, or design effort where the stakes are medium or higher.
3 questions only (Purpose, Success, Scope). No L4 research unless the human asks. No Round 2. Save is optional. Use for low-stakes daily decisions, personal-pillar exploration, fast topic framing, or when you just need a starting point.
Resume from where you left off. Check the Second Brain for any saved session state.
Display which levels have been completed, what decisions were made, and what is next.
Save the full session output (decisions, research, deliverables) to the appropriate vault location.
Append a feedback note to ~/.claude/skills/think/feedback.jsonl:
python3 -c "
import json, datetime, sys
note = {
'ts': datetime.datetime.utcnow().isoformat(),
'topic': '<current session topic or empty>',
'text': sys.argv[1]
}
with open('/Users/jneaimi/.claude/skills/think/feedback.jsonl', 'a') as f:
f.write(json.dumps(note) + '\n')
print('Feedback saved.')
" "<user text>"No AskUserQuestion needed. Confirm with "Feedback saved." and continue.
Read saved /think sessions from ~/vault/knowledge/decisions/, ~/vault/knowledge/learnings/, and ~/vault/projects/*/decisions/. Parse frontmatter tags: for pillar references. Count sessions per pillar over the last N days (default: 30). Reference pillar definitions from ~/.claude/skills/think/pillars.md (file maintained by a parallel agent). Report format:
Last 30 days — pillars touched:
Work / Craft 9 sessions
Decisions 2 sessions
Identity / Direction 1 session
Health 0 sessions
Money 0 sessions
Relationships 0 sessions
Learning 0 sessions
Time / Energy 0 sessions
Faith 0 sessions
Imbalance: heavy on Work; six pillars untouched.
Suggestion: try /think on Health or Relationships this week.If pillars.md does not exist yet, use the list above as the default pillar set and note: "Using default pillar list — pillars.md not found."
This is always the first step. Do not skip it.
Context-aware skip rule: If the prior 5+ messages of the conversation clearly establish a domain (e.g., the user has been discussing architecture decisions, a specific codebase, or a product spec), skip the Domain detection question. Instead, announce inline:
"Detected domain: Code/Architecture — adjust if wrong, otherwise we will proceed."
Only ask the explicit Domain question when /think is invoked cold (no relevant prior context). Cold invocation: the first message of a session, or a topic that does not follow from what was discussed.
When the Domain question IS needed, use AskUserQuestion:
AskUserQuestion (1 question):
Question: "What type of thinking is this?"
Header: "Domain"
Options (propose the best fit first):
- [Detected domain] (Recommended) — [brief description]
- [Second most likely] — [brief description]
- [Third option] — [brief description]
(User can type freely to specify)Domain table:
| Domain | Signals |
|---|---|
| Legal/Agreement | MOU, contract, partnership, terms, NDA |
| Product/Feature | build, app, tool, feature, MVP, product |
| Research/Analysis | market, trend, understand, investigate |
| Code/Architecture | system, API, database, refactor, design |
| Decision | choose, decide, should I, compare options |
| Content/Writing | article, post, thread, newsletter, pitch |
| Business/Strategy | opportunity, revenue, growth, positioning |
| Learning/Skill | learn, study, master, understand how |
| Hiring/Team | hire, role, team, candidate, interview |
| Process/Workflow | automate, streamline, improve, optimize |
#### Quick mode — Round 1 only (3 questions)
AskUserQuestion (3 questions):
Q1 — PURPOSE, Q3 — SUCCESS, Q5 — SCOPEStop after Round 1. Proceed directly to a brief framing summary. No L4 research, no L3 deliverable, no save required. If the human asks to go deeper, switch to deep mode.
#### Deep mode — Round 1 (3 questions)
After domain is confirmed, ask the first three evaluative questions. The AI does NOT propose answers — options are directional framings to help the human think, not AI-proposed solutions. This is the key difference from /prebuild.
AskUserQuestion (3 questions):
Q1 — PURPOSE
"What is the purpose of this [agreement/product/decision/...]?"
Options — framing options, not answers:
- "[Domain-specific framing A]"
- "[Domain-specific framing B]"
- "[Domain-specific framing C]"
Q2 — RESOURCES
"What does each side bring?" / "What do you have vs. need?"
Options — scope framings:
- "[Resource framing A]"
- "[Resource framing B]"
Q3 — SUCCESS
"What does success look like?"
Options — outcome framings:
- "[Outcome A — ambitious]"
- "[Outcome B — practical]"
- "[Outcome C — minimal viable]"#### Deep mode — Round 2: Risk, Scope, Commitment (3 questions)
GATE: Round 2 is mandatory in deep mode. Do not produce a Level 3 deliverable until all 6 questions have answers. Do not skip Round 2 even if Round 1 answers seem sufficient.
AskUserQuestion (3 questions):
Q4 — RISK
"What are you afraid of?" / "What could go wrong?"
multiSelect: true
Options — common risks for this domain (4 options):
- "[Risk A — most likely]"
- "[Risk B — highest impact]"
- "[Risk C — often overlooked]"
- "[Risk D — domain-specific]"
Q5 — SCOPE
"What is in vs. out of scope?"
Options:
- "[Narrow scope]"
- "[Medium scope]"
- "[Broad scope]"
Q6 — COMMITMENT
"How deep are you going?"
Options:
- "[Light — exploration/test]"
- "[Medium — serious but reversible]"
- "[Heavy — full commitment / All-in]"#### Deep mode — Round 3: Epistemic Prompts (mandatory for Heavy commitment)
Round 3 is a single AskUserQuestion call with three epistemic prompts. It is mandatory when Q6 = Heavy or All-in. For Light/Medium commitment it is optional — offer it but do not block progress if the human skips.
AskUserQuestion (3 questions):
Q7 — ASSUMPTIONS
"What are you assuming to be true about this situation?"
(free-form — no options; the human writes their assumptions)
Q8 — REVERSIBILITY
"If this goes wrong, how hard is it to undo?"
Options:
- "Fully reversible — low stakes"
- "Partially reversible with cost"
- "Difficult to reverse — significant switching cost"
- "Irreversible — one-way door"
Q9 — FALSIFIABILITY
"What would change your mind?"
(free-form — no options; the human writes the falsifying condition)When the user types their own text instead of selecting an option, accept it as the answer. Do not prompt them to pick from the list again.
Rule: Treat any free-text response to an AskUserQuestion as a valid answer. Acknowledge it and check for downstream implications:
"Got it — you are saying [paraphrase of what they wrote]. Does that change anything else we should account for?"
Then continue to the next question or step.
Example:
After all rounds are complete, compile answers into a clear summary. If any answer was free-text (Argue mode), incorporate it exactly. If any answer is vague or contradicts another, use a follow-up AskUserQuestion to clarify — do not guess.
## Level 5 Summary
- **Purpose:** [compiled answer]
- **Resources:** [compiled answer]
- **Success:** [compiled answer]
- **Risks:** [compiled answer — list all selected]
- **Scope:** [compiled answer]
- **Commitment:** [compiled answer]
- **Assumptions:** [Q7 if answered]
- **Reversibility:** [Q8 if answered]
- **Falsifying condition:** [Q9 if answered]
Moving to Level 4: Analyze...Based on the human's Level 5 answers, perform relevant research:
best practices
Structure your analysis as:
Mandatory loop-back rule: After presenting the analysis, you MUST check whether any finding introduces a decision the human has not yet made. If yes, return to Level 5 with an AskUserQuestion before proceeding to Level 3. This loop-back is not optional — it must happen at least once per deep mode session.
If the analysis reveals no new decisions (genuinely none), explicitly state: "Level 4 complete — no new decisions surfaced. Proceeding to Level 3."
AskUserQuestion (1 question) — loop-back example:
Question: "[Specific new decision that emerged from analysis]"
Header: "New decision"
Options:
- "[Option A — based on research finding]"
- "[Option B — alternative based on research]"
- "[Option C — if applicable]"The L4↔L5 loop may repeat. Each loop produces a cleaner Level 3 deliverable.
Signs that a loop-back is required:
Before producing any Level 3 output, verify:
If any gate is unmet, do not produce the deliverable. Return to the missing step.
Match the format to the domain:
| Domain | Output Format |
|---|---|
| Legal/Agreement | Full document with clauses, structured sections |
| Product/Feature | Spec, architecture diagram, or working code |
| Research/Analysis | Structured report (use /research template if applicable) |
| Code/Architecture | Code files, diagrams, implementation plan |
| Decision | Decision record (use ADR template from Second Brain) |
| Content/Writing | Draft content in target format |
| Business/Strategy | Business plan, pitch, or strategy document |
| Learning/Skill | Learning plan with milestones |
| Process/Workflow | Workflow definition, automation scripts |
/research collection pipeline/brain patterns and templates/prebuild for the build phase/diagramAfter delivering the output:
Tailor depth to expertise:
In deep mode, offer a save prompt. In quick mode, save is optional — offer but do not block.
AskUserQuestion (1 question):
Question: "Where should we save this session's output?"
Header: "Save to"
Options:
- "[Most likely vault location based on domain]" (Recommended)
- "[Alternative location]"
- "Don't save — this was exploratory"Save location by type:
| Type | Location |
|---|---|
| Active project | ~/vault/projects/<project-name>/ |
| Decision record | ~/vault/knowledge/decisions/ |
| Learning/insight | ~/vault/knowledge/learnings/ |
| Research | ~/vault/knowledge/research/trends/ |
| Pattern/template | ~/vault/knowledge/patterns/ |
| Quick capture | ~/vault/inbox/ |
Always:
index.mdLegal/Agreement:
Product/Feature:
Decision:
Code/Architecture:
Content/Writing:
Business/Strategy:
Throughout the session, maintain awareness of which levels have been completed. When asked for a summary (/think summary), display:
## /think Session: [Topic]
Mode: [Deep / Quick]
### Level 5: Evaluate [status]
- Purpose: [one-line summary]
- Resources: [one-line summary]
- Success: [one-line summary]
- Risk: [one-line summary]
- Scope: [one-line summary]
- Commitment: [one-line summary]
- Assumptions / Reversibility / Falsifiability: [if answered]
### Level 4: Analyze [status] ([N] loops)
- Loop 1: [what was researched, what decisions emerged]
- Loop 2: [follow-up research, final decisions]
### Level 3: Apply [status]
- Deliverable: [what was produced]
### Level 2: Understand [status]
- Explanation: [delivered / skipped — human is expert]
### Level 1: Remember [status]
- Status: [not yet saved / saved to path]least Q1, Q3, Q5 (purpose, success, scope) via AskUserQuestion before proceeding.
to help them think; they provide the substance.
questions, Level 4 loop-backs, and Level 1 save decisions.
required rounds (all 6 in deep mode) and at least one L4↔L5 loop-back check.
new decisions. If found, return to Level 5 before proceeding. If none, state it explicitly.
picking an option, treat it as a valid answer. Paraphrase and continue.
announce the detected domain inline and skip the Domain detection question.
versions when domain-specific ones are clearer.
like "Now moving to Level 4" or "This is a Level 5 question — only you can decide."
Skip previews for abstract/directional questions.
/think is invoked by Claude (Skill toolauto-fired because context matched) rather than typed by the user, announce it on the first turn: "Auto-firing /think because [reason]. Reply 'no skip' to disable for this session." Auto-fire is often the right call, but silent auto-fire violates the framework's first principle — the human must know they are entering Level 5. Historical data: ~40% of /think invocations (10 of 25 across 2026-03-16 → 2026-04-25) were auto-fires. Make activation visible.
L1-L3 output sits below the trust boundary because it has an external referent: the source document exists, the code runs or fails, the cited fact can be checked. Verification is possible.
L4-L6 output sits above the trust boundary because the ground truth is the human's judgment and values. No external source can confirm that the right trade-off was made, that the risk priority matches actual stakes, or that the direction aligns with what the human cares about. Only the human holds that ground truth.
This is the framework's central reframe: the AI is not "helping with the hard parts" above the boundary — it is assisting a process whose correctness only the human can validate. When the human rubber-stamps L4-L6 output without genuine evaluation, the collaboration fails even if the output looks sophisticated.
These are known ways /think breaks down:
(a) Human cannot competently audit Level 3 output. If the deliverable is in a domain where the human has no ability to evaluate correctness (e.g., a legal document in an unfamiliar jurisdiction), L3 output may pass unverified. Mitigation: the Level 2 explanation step exists specifically for this — always run it for unfamiliar domains.
(b) AI confidently wrong at L1, source not checked. The AI recalls training data with apparent confidence whether it is correct or not. If a recalled fact is not verified against a primary source, the entire downstream chain rests on a potentially incorrect foundation. Mitigation: flag any L1 claim that could be jurisdiction-specific, version-specific, or rapidly-changing.
(c) L5 questions answered superficially. When the human picks the first option quickly without genuine reflection, Level 5 becomes a checkbox rather than an evaluation. The output will then reflect the path of least resistance, not the human's actual goals. Mitigation: if answers come back in under 10 seconds for all six questions, surface one follow-up before proceeding.
(d) L4 skipped because output looks "good enough." If the Level 5 summary already sounds complete, it is tempting to jump straight to Level 3. The L4 research step frequently surfaces contradictions or missing information that would otherwise produce a flawed deliverable. Skipping it is the most common source of rework. Mitigation: the Level 3 gate enforces this structurally.
(e) Downstream agents drift from /think-derived decisions. When a /think session produces a decision that is passed to another agent (architect, developer, content drafter), the agent may receive only the deliverable and not the evaluation context behind it. Subsequent choices by that agent may silently contradict the L5 decisions. Mitigation: always save the full Level 5 Summary (not just the deliverable) and link it in the handoff note to downstream agents.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.