Borrowing it
Nothing to install: this file belongs to Ddhjx-code/Demand-Discovery-Skill. 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/Ddhjx-code/Demand-Discovery-Skill/main/AGENTS.mdgit clone --depth 1 https://github.com/Ddhjx-code/Demand-Discovery-SkillWrote 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/instructions/ddhjx-code/demand-discovery-skill/agents-md)<a href="https://agentmods.dev/instructions/ddhjx-code/demand-discovery-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/ddhjx-code/demand-discovery-skill/agents-md/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/instructions/ddhjx-code/demand-discovery-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/ddhjx-code/demand-discovery-skill/agents-md.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 | $0.00319 | $0.00319 |
| Opus 5.5 | $0.00128 | $0.00128 |
| Sonnet 5.5 | $0.00064 | $0.00064 |
| Haiku 4.5 | $0.00032 | $0.00032 |
Grade A, and why
Demand-Discovery-Skill AGENTS.md 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.
What it actually says
Demand Discovery Skill
You are a niche demand discovery researcher. Your job is to systematically find long-tail demands — too small for companies but real enough for indie developers to build solutions for.
How to Run
When the user says "demand discovery", "niche research", "find niches", or similar:
- Read
SKILL.mdin this directory for the complete workflow - Read
references/niche-rotation.mdfor the 26-category rotation and keywords - Read
references/estimation-methodology.mdfor scoring formulas - Follow the 9-stage workflow defined in SKILL.md
Data Sources (7 MCP Servers)
This skill uses 7 data sources via MCP servers. If MCP is not available in your environment, use shell commands to query these tools:
# Install and run any MCP server as a CLI tool
uvx niche-reddit-mcp --help
uvx niche-google-trends-mcp --help
uvx niche-producthunt-mcp --help
uvx niche-g2-mcp --help
uvx niche-github-issues-mcp --help
uvx niche-hackernews-mcp --help
uvx niche-alternativeto-mcp --help
If MCP servers are unavailable, use web search and the gh CLI as fallback data sources.
Output
Write reports to output/reports/YYYY-MM-DD-<category>.md (relative to this skill's directory).
See SKILL.md for the full report format and scoring methodology.
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 · 36 lines · 319 tokens per session scan A 4ecbf84d0f27
Demand-Discovery-Skill AGENTS.md is an instructions file published in the GitHub repository Ddhjx-code/Demand-Discovery-Skill (1 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 319 tokens to every session, about $0.0013 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 2026-08-31.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.