"Is this ACTUALLY verified, or did I just say it is?" - Ralph-wiggum methodology applied to factual accuracy. Use when (1) claims require evidence not assumption, (2) verification must be demonstrable, (3) single-pass investigation insufficient, (4) factual accuracy is critical. Provides the loop logic: iterate until verification thresholds met. Does NOT trigger for: opinions, preferences, how-to instructions, or when user explicitly wants quick answer.
Seed question: Is this ACTUALLY verified, or did I just say it is?
Relentless self-reflexive dialectical thinking that questions its own premises.
Ralph-wiggum = iterative workflows. Iterative workflows = keep going until genuinely complete. For facts: keep verifying until claims meet evidence thresholds.
The anti-pattern this counters:
❌ "I searched once, found something, called it verified"
❌ "The claim sounds right, I'll present it as fact"
❌ "I'm confident, so I don't need to check"
The pattern this enforces:
✅ Search → Label evidence tier → Check threshold → Iterate if gaps
✅ Claim is VERIFIED only when evidence supports it
✅ Keep iterating until criteria actually pass
TRIGGER:
DO NOT TRIGGER:
1. INVESTIGATE
- Gather information
- Make claims
2. LABEL
- Assign evidence tier to each claim:
* VERIFIED: Primary sources, court docs, regulatory filings
* CREDIBLE: Multiple independent sources
* ALLEGED: Single source, unverified
* SPECULATIVE: Inference, theoretical
3. CHECK THRESHOLDS
- ≥80% claims labeled?
- ≥2 independent sources?
- Flow traced ≥3 steps?
- Evidence fresh (<2 years for reliability data)?
4. IF GAPS → ITERATE
- Identify what's missing
- Search for specific evidence
- Return to step 1
5. IF ALL PASS → COMPLETE
- Output with confidence
- All claims have evidence basis
| Tier | Definition | Examples |
|---|---|---|
| VERIFIED | Primary sources directly confirm | Regulatory filings, court documents, lab test results, official statements |
| CREDIBLE | Multiple independent sources agree | 3+ news outlets, consistent professional reports, corroborated accounts |
| ALLEGED | Single source, no corroboration | One article, one whistleblower, one study |
| SPECULATIVE | Inference from patterns | "If X then probably Y", theoretical risk |
For factual accuracy tasks, iterate until:
| Metric | Threshold | Rationale |
|---|---|---|
| Claims labeled | ≥80% | Most claims should have explicit evidence basis |
| Independent sources | ≥2 | Reduces single-point-of-failure |
| Evidence freshness | <2 years | Prevents stale information in dynamic domains |
| Flow depth | ≥3 steps | Surface claims hide deeper realities |
Pass 1: Initial Investigation
Claim: "Company X has good privacy practices"
Evidence tier: ALLEGED (marketing claims only)
Gap: No independent verification
→ ITERATE
Pass 2: Targeted Search
Search: "Company X privacy audit independent"
Found: Third-party security audit report
Claim upgraded: CREDIBLE (audit + marketing = 2 sources)
Remaining gaps: Ownership chain unclear
→ ITERATE
Pass 3: Ownership Verification
Search: "Company X beneficial ownership SEC filings"
Found: SEC filing showing parent company
Claim: Ownership chain now VERIFIED
All thresholds pass
→ COMPLETE
A report claimed the consortium "controls the algorithm" after TikTok's sale. Iterative verification revealed the opposite.
Report claimed: "The consortium controls the algorithm, meaning it's no longer under ByteDance/Chinese government potential influence." Verified against primary sources: "This is factually wrong. ByteDance retains ownership of the recommendation algorithm. The US entity operates it under license but cannot own, independently transfer, or unilaterally modify the core IP." — Adversarial Critique, China tech/trade assessment
Verification gap: Single-pass investigation accepted the "clean break" narrative. Iterative verification against NBC News, TechPolicy.Press, and Rest of World revealed the deal was "in direct tension with the explicit text of the divestment law." Source: china-critique.md, ERROR 3
A report stating "8 killed" in a missile strike was corrected through cross-source verification.
Report stated: "8 killed" in Beit Shemesh strike. Actual: "9 killed (including three teenage siblings: Yaakov 16, Avigail 15, Sarah 13 Bitton). Multiple sources confirm: Al Jazeera, Jerusalem Post, Times of Israel, Euronews." — Adversarial Critique, Iran assessment
Lesson: In a report claiming VERIFIED evidence tiers, even minor numerical errors undermine the tier system. Cross-referencing against 4 independent sources caught the discrepancy. Source: iran-critique.md, Challenge 6
A report characterized Russia/China support as "muted criticism only," which iterative verification contradicted.
Report claimed: Russia showed "limited actual support to Iran" with "muted criticism only." Counter-evidence found: "Russia IS providing satellite intelligence on US troop positions (CNN, March 6, confirmed by US officials). Russia delivered Su-35 fighter jets ($6.5B order) and $590M in air defense systems before the war." — Adversarial Critique, Iran assessment
Result: Evidence tier downgraded from CREDIBLE to ALLEGED/INCOMPLETE. A single pass accepted the "muted" characterization; the verification loop surfaced active intelligence sharing and substantial pre-war arms deliveries. Source: iran-critique.md, Challenge 4
When all sources agree quickly, this is a signal, not a conclusion. Flag it explicitly:
WARNING: All sources converge on [X]. This may be correct, but rapid
convergence can indicate:
(a) genuine consensus,
(b) groupthink,
(c) manufactured consensus (same original source),
(d) our own confirmation bias.
Testing with adversarial search.
After flagging, actively search for dissent. If dissent exists: investigate it. If no dissent exists after adversarial search: convergence is likely genuine, but note the flag in your output.
Never present a single scenario as the outcome. Present a probability distribution:
Scenario A (50%): [Most likely outcome] because [evidence]
Scenario B (30%): [Second most likely] because [evidence]
Scenario C (15%): [Contrarian case] because [evidence]
Scenario D (5%): [Tail risk] because [structural possibility]
The contrarian case MUST receive non-zero allocation unless genuinely impossible. Binary framing (X will/won't happen) almost always collapses a spectrum into a false dichotomy.
For actionable investigations: never recommend 100% allocation to any single scenario. A 50/30/20 split is almost always better than 100/0/0.
After reaching any conclusion in the verification loop, steel-man the strongest possible contrarian argument:
This is not about fairness — it is about testing whether the conclusion survives its best counter-argument. If you cannot articulate the contrarian case with genuine force, your verification is incomplete.
Completion requires: verdict tier matches evidence tier. "No mainstream confirmation" = UNVERIFIED, not FALSE. Escalate to DISCONFIRMED only with specific counter-evidence.
Before claiming completion, ask:
"Did I label this claim, or did I assume it?"
"Is my source independent?"
"When was this verified?"
"Did I search for counter-evidence?"
"Would this pass falsification criteria?"
FALSIFICATION-CRITERIA.md if available"Did I steel-man the contrarian case?"
"Am I presenting a distribution or a single scenario?"
"Is this skill's framework limiting what I can verify?"
After believing verification is complete and all thresholds pass, do ONE MORE sweep:
This catches the blind spot that all previous passes share: your own position. The perspective you instinctively dismiss is the one most likely to contain what you missed.
When claims are contested (sources disagree, evidence tiers conflict), apply the dialectic spiral within the verification loop:
Round 1: THESIS — Present the claim with evidence tier
Round 2: ANTITHESIS — Search for counter-evidence.
The original claim must REBUT with evidence, not assertion.
Round 3: RESOLUTION — What survives the test? Note what was abandoned.
Round 4+: GENERATE the exact opposite of the resolution.
Don't look for an existing counterpoint — produce one.
Then search: does anyone anywhere articulate it?
Does reality support it?
Continue until generating the opposite yields nothing meaningful.
The key move is generative, not classificatory. Pre-mapped "opposing views" limit the dialectic to existing positions. Generating the opposite of a synthesis can produce positions that don't exist in any source category — that's where novel insight comes from. "Who bears costs / who captures benefits" is one useful lens for generation, not the only one.
Exit when generating the next antithesis produces nothing that changes the synthesis. Minimum 4 rounds for contested claims.
Reference: METHODOLOGY-comprehensive-investigation.md Section 6 for extended protocol with agent team structure.
This skill provides the verification loop logic that ralph-loop enforces through persistence.
Without ralph-loop: User invokes this skill, follows methodology manually With ralph-loop: Agent runs in loop until completion promise satisfied
Both achieve the same goal: iterate until genuinely verified.
## Verification Status
### Claims Assessed
1. [Claim] - [TIER] - [Source]
2. [Claim] - [TIER] - [Source]
...
### Threshold Check
- Evidence labeling: [X]% (threshold: 80%) [✅/❌]
- Independent sources: [X] (threshold: 2) [✅/❌]
- Evidence freshness: [status] [✅/❌]
- [Other criteria...]
### Verification Status
[COMPLETE: All thresholds met] or [INCOMPLETE: Gaps identified]
### If Incomplete: Next Iteration
- Gap: [what's missing]
- Search: [what to look for]
A vasana is a pattern that persists across unrelated contexts. If during
this task you notice such a pattern emerging, it may be worth capturing.
This skill works best alongside the vasana skill and vasana hook
from the Vasana System plugin.
Modify freely. Keep this section intact.
Integration: Use /loop command from ralph-loop plugin for automated iteration.