FPF Reasoning
VerifiedFalsification-based problem-solving with hypothesis generation and verification
$ Add to .claude/skills/ About This Skill
# Evidence Freshness Management
Manages evidence freshness by identifying stale decisions and providing governance actions. Implements FPF B.3.4 (Evidence Decay).
Key principle: Evidence is perishable. Decisions built on expired evidence carry hidden risk.
---
Quick Concepts
What is "stale" evidence?
Every piece of evidence has a `valid_until` date. A benchmark from 6 months ago may no longer reflect current system performance. A security audit from before a major dependency update doesn't account for new vulnerabilities.
When evidence expires, the decision it supports becomes questionable - not necessarily wrong, just unverified.
What is "waiving"?
Waiving = "I know this evidence is stale, I accept the risk temporarily."
- Use it when:
- You're about to launch and don't have time to re-run all tests
- The evidence is only slightly expired and probably still valid
- You have a scheduled date to refresh it properly
A waiver is NOT ignoring the problem - it's explicitly documenting that you know about the risk and accept it until a specific date.
The Three Actions
| Situation | Action | What it does | |-----------|--------|--------------| | Evidence is old but decision is still good | Refresh | Re-run the test, get fresh evidence | | Decision is obsolete, needs rethinking | Deprecate | Downgrade hypothesis, restart evaluation | | Accept risk temporarily | Waive | Record the risk acceptance with deadline |
---
Action (Run-Time)
Step 1: Generate Freshness Report
- List all evidence files in `.fpf/evidence/`
- For each evidence file:
- - Read `valid_until` from frontmatter
- - Compare with current date
- - Classify as FRESH, STALE, or EXPIRED
Step 2: Present Report
```markdown ## Evidence Freshness Report
EXPIRED (Requires Action)
| Evidence | Hypothesis | Expired | Days Overdue | |----------|------------|---------|--------------| | ev-benchmark-2024-06-15 | redis-caching | 2024-12-15 | 45 | | ev-security-2024-07-01 | auth-module | 2025-01-01 | 14 |
STALE (Warning)
| Evidence | Hypothesis | Expires | Days Left | |----------|------------|---------|-----------| | ev-loadtest-2024-10-01 | api-gateway | 2025-01-20 | 5 |
FRESH
| Evidence | Hypothesis | Expires | |----------|------------|---------| | ev-unittest-2025-01-10 | validation-lib | 2025-07-10 |
WAIVED
| Evidence | Waived Until | Rationale | |----------|--------------|-----------| | ev-perf-old | 2025-02-01 | Migration pending | ```
Step 3: Handle User Actions
Based on user response, perform one of:
#### Refresh
User: "Refresh the redis caching evidence"
- Navigate to the hypothesis in `.fpf/knowledge/L2/`
- Re-run validation to create fresh evidence
#### Deprecate
User: "Deprecate the auth module decision"
- Move hypothesis from L2 to L1 (or L1 to L0)
- Create deprecation record:
```markdown # In .fpf/evidence/deprecate-auth-module-2025-01-15.md --- id: deprecate-auth-module-2025-01-15 hypothesis_id: auth-module action: deprecate from_layer: L2 to_layer: L1 created: 2025-01-15T10:00:00Z ---
# Deprecation: auth-module
Reason: Evidence expired, technology landscape changed
Next Steps: Run `/fpf:propose-hypotheses` to explore alternatives ```
- Move the hypothesis file:
- ```bash
- mv .fpf/knowledge/L2/auth-module.md .fpf/knowledge/L1/auth-module.md
- ```
#### Waive
User: "Waive the benchmark until February"
- Create waiver record:
```markdown # In .fpf/evidence/waiver-benchmark-2025-01-15.md --- id: waiver-benchmark-2025-01-15 evidence_id: ev-benchmark-2024-06-15 waived_until: 2025-02-01 created: 2025-01-15T10:00:00Z ---
# Waiver: ev-benchmark-2024-06-15
Evidence: ev-benchmark-2024-06-15 Hypothesis: redis-caching Waived Until: 2025-02-01 Rationale: Migration pending, will re-run after completion
Accepted By: User Created: 2025-01-15
WARNING: This evidence returns to EXPIRED status after 2025-02-01. ```
---
Natural Language Usage
You don't need to memorize evidence IDs. Just describe what you want.
Example Workflow
``` User: /fpf:decay
Agent shows report with stale evidence
User: Waive the benchmark until February, we'll re-run it after the migration.
Agent: Creating waiver for ev-benchmark-2024-06-15 until 2025-02-01. Rationale: "Re-run after migration"
[Creates .fpf/evidence/waiver-benchmark-2025-01-15.md]
User: The vendor API is being discontinued. Deprecate that decision.
Agent: Deprecating hypothesis-vendor-api from L2 to L1. [Moves file, creates deprecation record]
Next step: Run /fpf:propose-hypotheses to explore alternatives. ```
---
WLNK Principle
A hypothesis is STALE if *any* of its evidence is expired (and not waived).
This is the Weakest Link (WLNK) principle: reliability = min(all evidence). One stale piece makes the whole decision questionable.
---
Audit Trail
All actions are logged:
| Action | What's Recorded | |--------|-----------------| | Deprecate | from_layer, to_layer, reason, date | | Waive | evidence_id, until_date, rationale, date |
- Files created in `.fpf/evidence/`:
- `deprecate-{hypothesis}-{date}.md`
- `waiver-{evidence}-{date}.md`
---
Common Workflows
Weekly Maintenance ``` /fpf:decay # See what's stale # For each stale item: refresh, deprecate, or waive ```
Pre-Release ``` /fpf:decay # Check for stale decisions # Either refresh evidence or explicitly waive with documented rationale # Waiver rationales become part of release documentation ```
After Major Change ``` # Dependency update, API change, security advisory... /fpf:decay # See what's affected # Deprecate obsolete decisions # Start new hypothesis cycle for replacements ```
Use Cases
- Apply the FPF (First Principles Framework) methodology to problem solving
- Break down complex problems into fundamental components for analysis
- Generate solutions by reasoning from first principles rather than analogy
- Build structured thinking workflows for strategic decision making
- Apply systematic problem decomposition to engineering and business challenges
Pros & Cons
Pros
- +Compatible with multiple platforms including claude-code, codex, gemini, cursor
- +Well-documented with detailed usage instructions and examples
- +Purpose-built for documentation & writing tasks with focused functionality
Cons
- -No built-in analytics or usage metrics dashboard
- -Configuration may require familiarity with documentation & writing concepts
FAQ
What does FPF Reasoning do?
What platforms support FPF Reasoning?
What are the use cases for FPF Reasoning?
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