Status

NeoLabHQ/context-engineering-kit/antigravity/skills/status

by NeoLabHQ23e2428e809d77717f8acc9659c374a3a1fcb93eNo licenseListed Oct 9, 2026Updated Oct 9, 2026

Display the current state of the FPF knowledge base

Instructions onlyProductivity & Workflow
AI-generated overview

Displays the current state of an FPF knowledge base, including hypothesis counts, evidence freshness and phase.

What it does
Inspects the .fpf/ directory structure and counts hypothesis files across the L0, L1, L2 and invalid knowledge layers. It checks evidence files in .fpf/evidence/ for freshness using their valid_until frontmatter field and counts decision records in .fpf/decisions/. It then reports a formatted status summary with phase detection, counts, evidence status, warnings and recent decisions.
When to use it
Use it when you need an overview of an FPF knowledge base's current state or want to know which workflow phase it is in. It is also useful for spotting stale or expired evidence and deciding whether to run follow-up commands such as decay or propose-hypotheses.
Requirements
No scripts or special tooling; it relies on the agent reading the .fpf/ directory and its files. The knowledge base must exist for a full report, though the skill also handles the not-initialized case.

Status Check

Display the current state of the FPF knowledge base.

Action (Run-Time)

  1. Check Directory Structure: Verify .fpf/ exists and contains required subdirectories.
  2. Count Hypotheses: List files in each knowledge layer:
    • .fpf/knowledge/L0/ (Proposed)
    • .fpf/knowledge/L1/ (Verified)
    • .fpf/knowledge/L2/ (Validated)
    • .fpf/knowledge/invalid/ (Rejected)
  3. Check Evidence Freshness: Scan .fpf/evidence/ for expired evidence.
  4. Count Decisions: List files in .fpf/decisions/.
  5. Report to user.

Status Report Format

markdown
## FPF Status
### Directory Structure- [x] .fpf/ exists- [x] knowledge/L0/ exists- [x] knowledge/L1/ exists- [x] knowledge/L2/ exists- [x] evidence/ exists- [x] decisions/ exists
### Current PhaseBased on hypothesis distribution: ABDUCTION | DEDUCTION | INDUCTION | DECISION | IDLE
### Hypothesis Counts
| Layer | Count | Status ||-------|-------|--------|| L0 (Proposed) | 3 | Awaiting verification || L1 (Verified) | 2 | Awaiting validation || L2 (Validated) | 1 | Ready for decision || Invalid | 1 | Rejected |
### Evidence Status
| Total | Fresh | Stale | Expired ||-------|-------|-------|---------|| 5 | 3 | 1 | 1 |
### Warnings
- 1 evidence file is EXPIRED: ev-benchmark-old-2024-06-15- Consider running `/fpf:decay` to review stale evidence
### Recent Decisions
| DRR | Date | Winner ||-----|------|--------|| DRR-2025-01-15-use-redis | 2025-01-15 | redis-caching |

Phase Detection Logic

Determine current phase by examining the knowledge base state:

ConditionPhaseNext Step
No .fpf/ directoryNOT INITIALIZEDRun /fpf:propose-hypotheses
L0 > 0, L1 = 0, L2 = 0ABDUCTIONContinue with verification
L1 > 0, L2 = 0DEDUCTIONContinue with validation
L2 > 0, no recent DRRINDUCTIONContinue with audit and decision
Recent DRR existsDECISION COMPLETEReview decision
All emptyIDLERun /fpf:propose-hypotheses

Evidence Freshness Check

For each evidence file in .fpf/evidence/:

  1. Read the valid_until field from frontmatter
  2. Compare with current date
  3. Classify:
    • Fresh: valid_until > today + 30 days
    • Stale: valid_until > today but < today + 30 days
    • Expired: valid_until < today

If any evidence is stale or expired, warn the user and suggest /fpf:decay.

Example Output

## FPF Status
### Current Phase: DEDUCTION
You have 3 hypotheses in L0 awaiting verification.Next step: Continue the FPF workflow to process L0 hypotheses.
### Hypothesis Counts
| Layer | Count ||-------|-------|| L0 | 3 || L1 | 0 || L2 | 0 || Invalid | 0 |
### Evidence Status
No evidence files yet (hypotheses not validated).
### No Warnings
All systems nominal.

Source and attribution

Source:NeoLabHQ/context-engineering-kitinantigravity/skills/statusat commit23e2428

License: No license

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