Goal-driven execution supervisor for complex multi-step work: keeps an explicit goal ledger, runs execute→validate→repair→revalidate, blocks premature or lazy completion, maintains PROJECT-CHECKPOINT.md, and resumes interrupted work from the latest verified state. Use when the user asks to complete,
编程
pbl-loop
试用Use when the user asks for learning goals, capability development, reflection, teaching, replication, transfer readiness, or applying a PBL loop in a real project context. Operate in exactly three modes, start, checkpoint, transfer, to separate delivery evidence from capability evidence and track provenance.
它能做什么
Use when the user asks for learning goals, capability development, reflection, teaching, replication, transfer readiness, or applying a PBL loop in a real project context. Operate in exactly three modes, start, checkpoint, transfer, to separate delivery evidence from capability evidence and track provenance.
技能文档
PBL Loop (v0.1)
Use this skill for capability-learning loops in real work. It is host-neutral and dependency-free.
Trigger and boundary
Trigger only when the user explicitly requests:
- a learning goal or capability-development objective,
- reflection on what was learned versus what was delivered,
- transfer, teaching, or replication against an adjacent problem,
- a PBL-style growth loop in project context.
Do not trigger for:
- routine project status updates,
- delivery planning without learning/evidence intent,
- generic study explanations,
- final completion checks without a capability loop,
- requests to change project truth or governance state directly.
Keep exactly three modes: start, checkpoint, transfer.
Start response contract (mandatory)
Treat start as a learning contract, not a full project plan.
If any key context is missing for:
- delivery goal,
- capability goal,
- evidence context,
complete the mandatory schema with explicit unknown values, then ask exactly one focused question. Do not ask additional questions or add a full project plan. The response must end with that question.
When context is sufficient:
- preserve the exact user delivery goal,
- record one bounded user-facing capability goal,
- keep all non-user-supplied details out of evidence fields,
- never invent counts, durations, thresholds, percentages, score bands, windows, deadlines, or acceptance gates,
- mark assistant additions as
source_status: proposedand never convert them into hard requirements.
Core invariants (v0.1)
- This skill is host-neutral. It does not require a specific host, CLI, MCP, fixed filesystem path, state backend, or external platform account.
- It does not require host metadata or proprietary runtimes.
- Preserve the real project delivery goal from user context. If unavailable, set
delivery_goaltounknownand set status explicitly. - Use item-level
source_statusfor each goal, requirement, proposal, unknown, and evidence item:user_statedunknownproposed
- Use item-level
evidence_statusfor each evidence item:observedinferredconfirmedunknown
- Track
assistance_provenancefor every claim/step:humanai_reasoningai_toolexternal_evidence
- Distinguish evidence classes:
- delivery evidence: shipped outputs, tests, artifacts, schedules, outcomes, acceptance signals.
- capability evidence: repeatability, reasoning quality, transfer performance, teachability.
- Default operation is conversation-only and stateless.
- If the user authorizes persistence, store only user-approved notes in a user/host-selected project-local location.
- Never overwrite prior project truth.
Four cognitive quadrants (state model)
Use these labels only for first-person capability/mastery claims, never for project status.
known-known: user-confirmed capability with sufficient repeated, independent, or transfer evidence.known-unknown: named capability gap with defined test path but insufficient proof.unknown-known: repeated behavior indicates likely capability not yet recognized.unknown-unknown: anomaly or gap with no clear shape/test path yet.
Rules:
- Move from
unknown-knownonly when behavior suggests likely capability and is explicitly documented. - Move to
known-unknownonly when a gap is named and testable. - Move to
known-knownonly after user-confirmed repeatable and transferable evidence.
Output schema (mandatory, all modes)
For every mode response, keep these top-level fields:
modedelivery_goallearning_goaluser_stated_requirementsassistant_proposalsunknownsassistance_provenancecapability_debtnext_deliberate_challengequadrant_beforeand/orquadrant_afterdelivery_evidencecapability_evidence
Each delivery_goal, learning_goal, user_stated_requirements, assistant_proposals, unknowns, delivery_evidence, and capability_evidence item must retain:
source_statusevidence_statusassistance_provenance
assistant_proposals should be empty when no proposal is needed; otherwise every proposal item must be clearly marked with source_status: proposed.
mode: start
Minimum required fields:
modedelivery_goallearning_goalquadrant_beforeuser_stated_requirementsassistant_proposalsunknownsassistance_provenancecapability_debtnext_deliberate_challengedelivery_evidencecapability_evidence
Start logic:
- Restate the delivery goal with explicit status. If absent, set
delivery_goal: unknown. - Set one bounded first-person capability goal.
- Set baseline
quadrant_beforeonly for that capability claim. - Add user facts to
user_stated_requirements, missing context intounknowns. - Put assistant additions in
assistant_proposalswithsource_status: proposed. - Keep
delivery_evidenceandcapability_evidenceas empty lists when no evidence is available; never omit the mandatory fields. - If key context is still missing, end the response with exactly one focused question.
mode: checkpoint
- Carry forward the delivery goal and previous schema context.
- Add delivery/capability evidence updates and evidence status.
- Set
quadrant_afterto show capability movement. - Keep
capability_debtexplicit. - Set
next_deliberate_challengeand any decision needed before continuation.
mode: transfer
- Carry forward the delivery goal from context; do not redefine it as the transfer task.
- Define one bounded adjacent problem in the same capability family.
- Enforce original-answer leakage control and avoid revealing prior exact wording/artifacts.
- Evaluate transfer for adaptability, explanation quality, and reuse.
- Update
quadrant_before/quadrant_afterandcapability_debt. - Use
evidence_statusfor transfer judgments.
Anti-fabrication rule
- Do not fabricate counts, durations, percentages, score bands, 24-hour windows, full intervention plans, or acceptance gates when missing.
- Use
unknownorproposedstates instead of invented concrete values.
Fail-closed rule
Delivery polish and intervention quality do not prove capability. Capability claims still require evidence status and quadrant movement updates.
Optional companion note
FlowGrid (https://github.com/dlxeva/FlowGrid) is optional and only for durable cross-session judgment state when the user explicitly chooses it.
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