Borrowing it
Nothing to install: this file belongs to lowtidebuild/public-equity-research. 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/lowtidebuild/public-equity-research/main/.claude/skills/output-generator/SKILL.mdgit clone --depth 1 https://github.com/lowtidebuild/public-equity-researchWrote 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/lowtidebuild/public-equity-research/output-generator)<a href="https://agentmods.dev/skills/lowtidebuild/public-equity-research/output-generator"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/output-generator/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/lowtidebuild/public-equity-research/output-generator"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/output-generator.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 | $0.00000 | $0.01487 |
| Opus 5 | $0.00000 | $0.00744 |
| Sonnet 5 | $0.00000 | $0.00297 |
| Haiku 4.5 | $0.00000 | $0.00149 |
Grade A, and why
output-generator 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 10d 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Output Generator — SKILL.md
Role: Step 8 — Generate the final analysis output in the requested mode (A, B, C, D). Mode A delegates to briefing-generator; Mode B uses scripts/render-comparison.py; Mode C delegates to dashboard-generator; Mode D uses scripts/docx-generator.py.
Triggered by: CLAUDE.md after Analyst Agent (Step 7) completes
Reads: output/runs/{run_id}/{ticker}/analysis-result.json, appropriate mode template
Writes: File (Mode B, D); Mode A delegates to briefing-generator/SKILL.md; Mode C delegates to dashboard-generator/SKILL.md
References: mode-b-template.md, mode-d-template.md, scripts/render-comparison.py, scripts/docx-generator.py
Mode Routing
output_mode = "A" → Mode A: HTML briefing (delegate to briefing-generator/SKILL.md)
output_mode = "B" → Mode B: HTML file (this file, uses mode-b-template.md + scripts/render-comparison.py)
output_mode = "C" → Mode C: HTML dashboard (delegate to dashboard-generator/SKILL.md)
output_mode = "D" → Mode D: DOCX investment memo (this file, uses docx-generator.py)
Mode B — Comparative Matrix (HTML File)
Load mode-b-template.md. Populate from each ticker's run-local validated-data.json.
Preferred scripted path:
python .claude/skills/output-generator/scripts/render-comparison.py \
--input output/runs/{run_id}/{ticker}/analysis-result.json \
--output output/reports/{tickers}_B_{lang}_{YYYY-MM-DD}.html
render-comparison.py resolves peer analysis-result.json / validated-data.json files from
the run-local artifact root first, then falls back to peer-specific run-local legacy promotions,
and finally to immutable snapshot refs from output/data/{ticker}/latest.json if needed.
Pre-output checks:
- Same metric set applied to all peers?
- Winner column logic correct (low for valuation, high for growth)?
- R/R Score computed for all peers?
- Best Pick labeled as opinion?
- Key Differentiators have ≥2 specific numbers each?
Write to: output/reports/{tickers}_B_{lang}_{YYYY-MM-DD}.html
What ships with it
7 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.
- 10d ago First seen · 145 lines · 0 tokens per session scan A 8fecd32a66a5
output-generator is a skill published in the GitHub repository lowtidebuild/public-equity-research (46 stars, last pushed 1mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,487 tokens. 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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