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 agentmods add skills/resciencelab/opc-skills/requesthuntnpx skills add ReScienceLab/opc-skills --skill requesthuntgit clone --depth 1 https://github.com/ReScienceLab/opc-skillsWrote 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/resciencelab/opc-skills/requesthunt)<a href="https://agentmods.dev/skills/resciencelab/opc-skills/requesthunt"><img src="https://agentmods.dev/badge/skills/resciencelab/opc-skills/requesthunt.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 | $0.00065 | $0.02129 |
| Opus 5 | $0.00032 | $0.01064 |
| Sonnet 5 | $0.00013 | $0.00426 |
| Haiku 4.5 | $0.00006 | $0.00213 |
Grade C, and why
requesthunt scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -fsSL https://requesthunt.com/cli | sh Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://requesthunt.com/cli | sh How it starts
The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RequestHunt Skill
Generate user demand research reports by collecting and analyzing real user feedback from Reddit, X (Twitter), GitHub, YouTube, LinkedIn, and Amazon.
Prerequisites
Install the CLI and authenticate:
curl -fsSL https://requesthunt.com/cli | sh
requesthunt auth login
The installer downloads a pre-built binary from GitHub Releases and verifies its SHA256 checksum before installation. Alternatively, build from source with cargo install --path cli from the requesthunt-cli repository.
The CLI displays a verification code and opens https://requesthunt.com/device — the human must enter the code to approve. Verify with:
requesthunt config show
Expected output contains: resolved_api_key: with a masked key value (not null).
For headless/CI environments, set the API key via environment variable (preferred):
export REQUESTHUNT_API_KEY="$YOUR_KEY"
Or save it to the local config file (created with owner-only permissions):
requesthunt config set-key "$YOUR_KEY"
Get your key from: https://requesthunt.com/dashboard
Security: Never hardcode API keys directly in skill instructions or agent output. Use environment variables or the secured config file.
Output Modes
Default output is TOON (Token-Oriented Object Notation) — structured and token-efficient.
Use --json for raw JSON or --human for table/key-value display.
Platform Selection Guide
Each platform captures different types of user feedback. Choose platforms based on the product category to maximize signal quality.
Platform Strengths
| Platform | Best For | Signal Type | Typical Yield |
|---|---|---|---|
| YouTube | Consumer products, hardware, lifestyle apps | Specific feature asks from review/tutorial comments | High (10-29 per topic) |
| Developer tools, creator economy, niche communities | Deep technical discussions, long-tail needs | High for dev topics (up to 176) | |
| B2B software, healthcare, enterprise tools | Professional/industry opinions, market context | Low volume but high engagement | |
| X | Trending topics, quick sentiment signals | Fragmented feedback, emotional reactions | Low-medium (1-6 per topic) |
| GitHub | Open-source tools, developer infrastructure | Concrete bugs and feature requests from issues | High for OSS, zero for non-tech |
| Amazon | Consumer products, electronics, home goods | Product review complaints and feature wishes | High for physical products |
What ships with it
3 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.
- 4d ago First seen · 215 lines · 65 tokens per session scan C 3107b90ff342
requesthunt is a skill published in the GitHub repository ReScienceLab/opc-skills (1,747 stars, last pushed 2d ago), licensed Apache-2.0. It adds 65 tokens to every session and 2,129 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
context-okf-llm-ingest
Use when extracting a codebase's implementation decisions into Metatron with an LLM/agent instead of metatron ingest — authoring candidate decisions as Open Knowledge Format (OKF) markdown files locally for review.
context-okf-promote-candidates
Use when promoting reviewed Metatron candidate decisions to canonical in a git/CI flow — moving Open Knowledge Format (OKF) files from candidate/ to decisions/. The agent performs only human-named moves; it never decides what to promote.
live-audit
Audit steam-games-mcp — build/test/lint gate, live MCP tool edge-case sweep (input validation, SteamID64/vanity/appid edge cases, key-gating), and source-level code review. Use when asked to test/audit the published or just-fixed steam-games-mcp package, hunt for bugs/edge cases, or repeat "the same kind of testing as…
live-audit
Repo-specific playbook, for any agent/model working on this repo (not tied to a particular harness — see AGENTS.md's own framing). Use it when asked to test/audit/smoke-test the published tmdb-mcp package, hunt for bugs or edge cases, or repeat "the same kind of testing as before.".
prompt-check
Live-test every MCP Prompt in src/tools/prompts.ts through the real MCP protocol (not a static read) across every argument combination. Use when a prompt is added or its argument-handling logic changes, or as part of a live-audit pass.
prompt-check
Live-test every MCP Prompt in src/prompts.ts through the real MCP protocol (not a static read) across every argument combination, including every enum value. Use when a prompt is added or its argument-handling logic changes, or as part of a live-audit pass.