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 skills add genli-ai/market-research-skills --skill analyst-researchgit clone --depth 1 https://github.com/genli-ai/market-research-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/genli-ai/market-research-skills/analyst-research)<a href="https://agentmods.dev/skills/genli-ai/market-research-skills/analyst-research"><img src="https://agentmods.dev/badge/skills/genli-ai/market-research-skills/analyst-research/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/genli-ai/market-research-skills/analyst-research"><img src="https://agentmods.dev/badge/skills/genli-ai/market-research-skills/analyst-research.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 | $0.00240 | $0.02542 |
| Opus 5 | $0.00120 | $0.01271 |
| Sonnet 5 | $0.00048 | $0.00508 |
| Haiku 4.5 | $0.00024 | $0.00254 |
Grade A, and why
analyst-research 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 13d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
analyst-research · investment research workflow skill
A field-validated AI-assisted research workflow for investment analysts and policy researchers, packaged as a reusable Claude skill. Built on the methodology that produced the Saudi Vision 2030 deep-dive (35 figures, 15k+ words). Three scope modes; user picks at trigger time.
License: MIT. Copyright © 2026 Ligen [email protected]. See
LICENSE.
Step 0 — pick a mode (REQUIRED before loading references)
When this skill is triggered, before loading any reference file, ask the user to pick a scope. Present these three options verbatim:
This skill has three scope modes. Pick one based on your project size:
light 4-5 page decision memo, 0 charts, ~15 min budget
Single LLM session. Pure markdown footnote citations.
Use for: exec brief, internal memo, quick decision support.
medium 12-15 page topic analysis, 6-10 charts, ~1 h budget
Single LLM. PDF + Word derivations. Sign-off checkpoint after draft.
Use for: topic deep-dive, board memo with data, same-day analysis.
heavy Flagship report 30-40 pages / 15k+ words, 25-35+ charts, ~2-3 h budget
Single or multi-LLM. PDF + Word + WeChat md + HTML publication.
Runs the full 11-step staged workflow (framing → sourcing →
analysis → drafting → review), with 3 sign-off checkpoints.
Use for: industry deep-dive, macro thesis, policy assessment,
flagship investor publication.
Which mode fits your project? (reply with light, medium, or heavy)
If the user's trigger message already contains explicit scope hints (page count, chart count, time budget), infer the mode and ask one-line confirmation instead of presenting the full menu:
What ships with it
18 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.
- MODE_REGISTRY.md 4.4 KB
- MODE_REGISTRY.zh.md 4.1 KB
- references/_quarto-light.yml 2.1 KB
- references/_quarto-medium.yml 5.6 KB
- references/report_style_spec.md 65 KB
- references/report_style_spec.zh.md 61 KB
- references/workflow_heavy.md 116 KB
- references/workflow_heavy.zh.md 107 KB
- references/workflow_light.md 24 KB
- references/workflow_light.zh.md 21 KB
- references/workflow_medium.md 53 KB
- references/workflow_medium.zh.md 49 KB
- references/workflow.md 3.3 KB
- references/workflow.zh.md 2.9 KB
- scripts/author.jpg 13 KB
- scripts/chart_template.py 26 KB runs code
- scripts/publication-style-template.html 27 KB
- SKILL.zh.md 9.1 KB
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.
- 13d ago First seen · 151 lines · 240 tokens per session scan A 0f91d80d5c34
analyst-research is a skill published in the GitHub repository genli-ai/market-research-skills (62 stars, last pushed 3mo ago), licensed MIT. It adds 240 tokens to every session and 2,542 once invoked, about $0.0012 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 2026-08-30.
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