Borrowing it
Nothing to install: this file belongs to lowtidebuild/public-equity-research. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lowtidebuild/public-equity-research/main/.claude/skills/data-validator/SKILL.mdgit clone --depth 1 https://github.com/lowtidebuild/public-equity-researchWrote 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/lowtidebuild/public-equity-research/data-validator)<a href="https://agentmods.dev/skills/lowtidebuild/public-equity-research/data-validator"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/data-validator/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/lowtidebuild/public-equity-research/data-validator"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/data-validator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.04600 |
| Opus 5.5 | $0.00000 | $0.01840 |
| Sonnet 5.5 | $0.00000 | $0.00920 |
| Haiku 4.5 | $0.00000 | $0.00460 |
Grade A, and why
data-validator 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 1mo ago.
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 — 448 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Validator — SKILL.md
Role: Step 5 — Validate all collected data through 3-layer fact-checking, assign confidence grades, build the evidence pack, measure Analyst context budget, and enforce the Blank-Over-Wrong principle.
Triggered by: CLAUDE.md after Step 4 (web researcher)
Reads: output/runs/{run_id}/{ticker}/tier1-raw.json (Enhanced), output/runs/{run_id}/{ticker}/tier2-raw.json, references/validation-rules.md, references/confidence-grading.md, references/source-metadata-contract.md
Writes: output/runs/{run_id}/{ticker}/validated-data.json, output/runs/{run_id}/{ticker}/evidence-pack.json, output/runs/{run_id}/{ticker}/context-budget.json
References: validation-rules.md, confidence-grading.md, source-metadata-contract.md
THE BLANK-OVER-WRONG PRINCIPLE
빈칸 > 틀린 숫자 (An empty cell is better than a wrong number)
If a data point cannot be verified to Grade C or above, it is:
- Set to
nullin validated output - Listed in
exclusionswith reason - Displayed as "—" in all output modes
- NEVER filled with an estimate, approximation, or best guess
This principle is ABSOLUTE. No exceptions. Grade D = excluded.
Instructions
Step 5.1 — Load Data Sources
Enhanced Mode:
Load: output/runs/{run_id}/{ticker}/tier1-raw.json (API data)
Load: output/runs/{run_id}/{ticker}/tier2-raw.json (web data)
Primary source: tier1 (API)
Cross-check source: tier2 (web)
Standard Mode (US stocks):
Load: output/runs/{run_id}/{ticker}/tier2-raw.json (web data only)
Primary source: tier2 extracted_metric_candidates
Cross-check source: tier2 extracted_metric_candidates from independent source_domain values
Korean stocks:
Load: output/runs/{run_id}/{ticker}/dart-api-raw.json (DART OpenAPI — Grade A financials, always attempted)
Load: output/runs/{run_id}/{ticker}/tier2-raw.json (web — price from 네이버금융, consensus, qualitative)
Primary financial source: run-local dart-api-raw.json (if exists)
Primary market data source: tier2 (네이버금융)
Fallback: if dart-api-raw.json missing → tier2-raw.json only (aggregator-only, max Grade B)
What ships with it
6 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.
- 1mo ago First seen · 448 lines · 0 tokens per session scan A 6deaf6a01e70
data-validator is a skill published in the GitHub repository lowtidebuild/public-equity-research (47 stars, last pushed 3mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 4,600 tokens. 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 2026-08-30.
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