Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nealcaren/social-data-analysis --skill verifiergit clone --depth 1 https://github.com/nealcaren/social-data-analysisWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nealcaren/social-data-analysis/verifier)<a href="https://agentmods.dev/skills/nealcaren/social-data-analysis/verifier"><img src="https://agentmods.dev/badge/skills/nealcaren/social-data-analysis/verifier/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nealcaren/social-data-analysis/verifier"><img src="https://agentmods.dev/badge/skills/nealcaren/social-data-analysis/verifier.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.02724 |
| Opus 5.5 | $0.00016 | $0.01090 |
| Sonnet 5.5 | $0.00008 | $0.00545 |
| Haiku 4.5 | $0.00004 | $0.00272 |
Grade A, and why
verifier scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 336 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verifier
Script paths below are relative to this skill's base directory ($SKILL_DIR), which Claude Code reports when the skill loads.
You help researchers verify claims and quotes in their manuscripts against source materials. Given a draft manuscript and source documents, you systematically confirm that quoted text and attributed claims actually appear in the sources.
Project Integration
This skill reads from project.yaml when available:
# From project.yaml
type: qualitative # or quantitative, mixed
paths:
# For qualitative
transcripts: data/raw/
# For quantitative
raw_data: data/raw/
scripts: scripts/analysis/
Project type: This skill works for all project types:
- Qualitative: Verifies participant quotes against transcripts
- Quantitative: Verifies statistical claims against data/scripts
- Mixed: Handles both verification types
Updates progress.yaml when complete:
status:
verification: done
artifacts:
verification_report: verification/verification-report.md
File Management
This skill uses git to track progress across phases. Before modifying any output file at a new phase:
- Stage and commit current state:
git add [files] && git commit -m "verifier: Phase N complete" - Then proceed with modifications.
Do NOT create version-suffixed copies (e.g., -v2, -final, -working). The git history serves as the version trail.
What This Skill Does
This is a verification skill that catches errors before they become problems:
- Extract all direct quotes and verifiable claims from a manuscript
- Map each item to its purported source (interview, article, document)
- Verify each item is present in the source using efficient search
- Escalate to deep reading (haiku agent) when fast search fails
- Report verification status with issues flagged for review
When to Use This Skill
Use this skill when you have:
- A manuscript with quotes attributed to interview participants or literature
- Source materials available (transcripts, PDFs, or document folder)
- A need to confirm accuracy before submission
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 336 lines · 41 tokens per session scan A 94e30ba7da86
verifier is a skill published in the GitHub repository nealcaren/social-data-analysis (90 stars, last pushed 2d ago), licensed MIT. It adds 41 tokens to every session and 2,724 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-17.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
exploratory-data-analysis
Performs bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
matlab
Builds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
phylogenetics
Builds and analyzes phylogenetic trees using MAFFT multiple sequence alignment, IQ-TREE maximum likelihood with ModelFinder and branch support, and FastTree approximate inference. Uses ETE3 for tree summaries and visualization. Applies to homologous nucleotide or protein sequences, microbial gene trees, protein…
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
presenting-conference-talks
Generates conference presentation slides (Beamer LaTeX PDF and editable PPTX) from a compiled paper with speaker notes and talk script. Use when preparing oral talks, spotlight presentations, or invited talks for ML and systems conferences.