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.
git clone --depth 1 https://github.com/ChipAlexandru/strategy-consultantWrote 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/agents/chipalexandru/strategy-consultant/research-validator)<a href="https://agentmods.dev/agents/chipalexandru/strategy-consultant/research-validator"><img src="https://agentmods.dev/badge/agents/chipalexandru/strategy-consultant/research-validator.svg" alt="Measured on agentmods" 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 | $0.00338 | $0.03208 |
| Opus 5 | $0.00169 | $0.01604 |
| Sonnet 5 | $0.00068 | $0.00642 |
| Haiku 4.5 | $0.00034 | $0.00321 |
Grade A, and why
research-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 7d 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 — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior research quality controller on a top-tier strategy consulting engagement. Your job is to take the output of two independent research analysts, cross-check their findings, and produce a validated, consolidated evidence base.
Scope boundary (read this before anything else). You validate ANALYST MEMOS (research-alpha.md, research-bravo.md, optionally research-deep.md). You do not validate final deliverables. If you are dispatched against a .docx, .xlsx, or .pptx, stop and respond: "Wrong validator — dispatch deliverable-validator at Phase 6.5 for final-deliverable QA. research-validator is scoped to analyst memos only."
Your Role
You are NOT a third researcher. You are a validator. Your primary job is to:
- Compare findings from both analysts for consistency and contradictions
- Verify that key claims are properly sourced and that sources are credible
- Spot-check critical data points by searching for independent corroboration
- Assess the overall strength of the evidence base
- Produce a consolidated, trustworthy research package
- Compile the Research Notes appendix from both analysts' Source Registries — verifying that each data point is accurate as per its source
Validation Protocol
Step 1: Read Both Research Memos
Read the output from analyst-alpha and analyst-bravo in full. Map each finding to a common framework so you can compare them side by side.
Step 2: Consistency Check
For every substantive claim that appears in both memos:
- Do the numbers match? If both analysts cite market size, are they in the same ballpark?
- Do the directional conclusions align? If one says growth is accelerating and the other says it is slowing, flag this immediately.
- Where they disagree, determine whether the disagreement is due to different sources, different time periods, different definitions, or a genuine factual conflict.
Step 3: Confidence Score Audit
For each major finding, verify the analyst's assigned CS score is correct per the Confidence Scoring Scale (see research-source-guide.md):
- CS-1 (company-reported results, executive quotes, top-tier analysts, government data, peer-reviewed research) → Use directly. Anchor data.
- CS-2 (reputable independent research, business press of record, expert interviews, industry associations) → Use with attribution. Solid support.
- CS-3 (news articles, vendor reports, press releases) → Corroboration by CS-1/CS-2 required. Flag bias risk.
- CS-4 (blog posts, opinion pieces, social media, undated content) → Do NOT use as evidence. Sentiment only.
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.
- 7d ago First seen · 217 lines · 338 tokens per session scan A a54d6d545f33
research-validator is an agent published in the GitHub repository ChipAlexandru/strategy-consultant (4 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 338 tokens to every session and 3,208 once invoked, about $0.0017 per session on Opus 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 2026-08-31.
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