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/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/rules/ddhjx-code/demand-discovery-skill/demand-discovery)<a href="https://agentmods.dev/rules/ddhjx-code/demand-discovery-skill/demand-discovery"><img src="https://agentmods.dev/badge/rules/ddhjx-code/demand-discovery-skill/demand-discovery/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/rules/ddhjx-code/demand-discovery-skill/demand-discovery"><img src="https://agentmods.dev/badge/rules/ddhjx-code/demand-discovery-skill/demand-discovery.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 | $0.00016 | $0.00297 |
| Opus 5.5 | $0.00006 | $0.00119 |
| Sonnet 5.5 | $0.00003 | $0.00059 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
demand-discovery 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
When the user asks for "demand discovery", "niche research", "find niches", or similar:
- Read
SKILL.mdfor the complete 9-stage workflow - Read
references/niche-rotation.mdfor the 26-category rotation with keywords - Read
references/estimation-methodology.mdfor scoring formulas
Data Sources
Use web search to gather data from these 7 sources:
- Reddit — Search for pain points in category-relevant subreddits
- G2 — Find competitor low-star reviews
- Product Hunt — Discover trending alternatives
- GitHub Issues — Find feature requests with high reaction counts
- Hacker News — Analyze developer discussions (use hn.algolia.com API)
- AlternativeTo — Map software alternatives and gaps
- Google Trends — Validate search volume trends
Output
Write reports to output/reports/YYYY-MM-DD-<category>.md (relative to this skill's directory) following the format in SKILL.md.
Scoring
Each demand gets a composite score (0-100) from weighted signals across all 7 sources, plus a feasibility score (1-5). See references/estimation-methodology.md for formulas.
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 · 32 lines · 16 tokens per session scan A 536616f7327f
demand-discovery is a cursor rule published in the GitHub repository Ddhjx-code/Demand-Discovery-Skill (1 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 16 tokens to every session and 297 once invoked, about $0.0001 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.
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