Best use case
fpf:status is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Display the current state of the FPF knowledge base
Teams using fpf:status should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/status/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How fpf:status Compares
| Feature / Agent | fpf:status | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Display the current state of the FPF knowledge base
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 Phase
Based 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:
| Condition | Phase | Next Step |
|-----------|-------|-----------|
| No `.fpf/` directory | NOT INITIALIZED | Run `/fpf:propose-hypotheses` |
| L0 > 0, L1 = 0, L2 = 0 | ABDUCTION | Continue with verification |
| L1 > 0, L2 = 0 | DEDUCTION | Continue with validation |
| L2 > 0, no recent DRR | INDUCTION | Continue with audit and decision |
| Recent DRR exists | DECISION COMPLETE | Review decision |
| All empty | IDLE | Run `/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.
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