flonat/flonat-research/weakness-scanner
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Identify recurring weak arguments, unsupported assumptions, and vulnerable inference patterns across a literature corpus. Use when stress-testing a body of work rather than reviewing one manuscript. For one paper's argument, use the appropriate paper-review workflow.
Install
npx vskill@latest install flonat/flonat-research/weakness-scannerSKILL.md
Weakness Scanner
Identify the weakest arguments made across a body of literature. Find logical flaws, data limitations, unsupported claims, and findings contradicted by other work. Your contribution section writes itself after this.
Unlike devils-advocate (which stress-tests YOUR argument), this skill scans OTHER people's work for vulnerabilities. It's how you find the gap your paper fills.
When to Use
- Before writing your contribution section — need to know what's broken in prior work
- Identifying research opportunities — weak arguments = space for new work
- Preparing a rebuttal or response — need to show where existing claims fall short
- Deciding which papers to build on vs. which to challenge
When NOT to Use
- Your own paper — use
devils-advocateor thepaper-criticagent - Full peer review — use the
referee2-revieweragent - Methodological comparison — use
method-audit(overlaps, but different focus)
Input
Same corpus inputs: .bib file, PDF directory, topic, or paper list. Works best with 10-20 papers on a focused topic.
Workflow
Phase 1: Corpus Assembly
Same as other corpus skills. Prioritise empirical papers making causal or strong claims — these are most likely to have exploitable weaknesses.
Phase 2: Weakness Extraction
For each paper (read via split-pdf), look for:
- Logical flaws
- Non sequiturs — conclusions that don't follow from the evidence
- Circular reasoning — assuming what they're trying to prove
- False dichotomies — presenting only two options when more exist
- Hasty generalisation — drawing broad conclusions from narrow evidence
- Data limitations
- Small samples without power analysis
- Non-representative populations with claims of generalisability
- Measurement issues (self-report bias, proxy variables)
- Missing data handled without sensitivity analysis
- Identification problems
- Causal claims from observational data without credible identification
- Omitted variable bias acknowledged but not addressed
- Reverse causality not ruled out
- Weak instruments (if IV)
- Contradicted claims
- Findings that conflict with other papers in the corpus
- Claims undermined by the authors' own robustness checks
- Results that don't survive alternative specifications
- Rhetorical overreach
- Abstract claims stronger than the evidence supports
- Policy recommendations not grounded in the findings
- "First to study X" claims that ignore prior work
Phase 3: Cross-Paper Validation
For each weakness identified:
- Check if other papers in the corpus have already flagged it
- Search for papers that contradict the weak claim (use
scholarly scholarly-search) - Check if the weakness has been addressed in subsequent work by the same authors
Phase 4: Severity Ranking
Rank all weaknesses by severity:
| Severity | Criteria | |
|---|---|---|
| Fatal | The core finding is likely wrong — the paper's contribution doesn't hold | |
| Serious | A major limitation that significantly qualifies the findings | |
| Moderate | A real limitation that the authors should have discussed | |
| Minor | A weakness that doesn't undermine the main claims |
Phase 5: Output
Write to WEAKNESS-SCAN.md in the project directory.
Output Format
Cross-References
| Skill | When to use instead/alongside | |
|---|---|---|
devils-advocate | To stress-test YOUR argument (this scans others') | |
method-audit | For systematic methodological comparison (less adversarial) | |
theory-mapper | To understand which theories underpin the weak arguments | |
replication-audit | To check which findings have actually been replicated |
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/weakness-scanner/SKILL.md
Popularity
- Repository stars
- 119
- Repository forks
- 21
- 7-day trend score
- 24
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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