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/dashboard-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/dashboard-generator)<a href="https://agentmods.dev/skills/lowtidebuild/public-equity-research/dashboard-generator"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/dashboard-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/dashboard-generator"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/dashboard-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.03442 |
| Opus 5 | $0.00000 | $0.01721 |
| Sonnet 5 | $0.00000 | $0.00688 |
| Haiku 4.5 | $0.00000 | $0.00344 |
Grade A, and why
dashboard-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 — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dashboard Generator — SKILL.md
Role: Step 8 — Generate the Mode C HTML dashboard from analysis-result.json.
Triggered by: CLAUDE.md when output_mode = "C" after Step 7 (Analyst Agent completes analysis)
Reads: run-local analysis-result.json, references/html-template.md, references/color-system.md
Writes: output/reports/{ticker}_C_{lang}_{YYYY-MM-DD}.html
References: html-template.md, color-system.md, docs/adr/0001-mode-c-rendering-strategy.ko.md
Instructions
Step 8.1 — Load Inputs
Load in this order:
- Read
references/html-template.md— complete HTML skeleton with all 11 sections - Read
references/color-system.md— Tailwind CSS classes and Chart.js color configs - Read run-local
analysis-result.json— analysis output from Analyst Agent - Verify all required sections are present in run-local
analysis-result.json
Step 8.2 — Compute Data Confidence Indicator
From run-local analysis-result.json, count the data_quality_used grade distribution:
Grade A count: {N}
Grade B count: {N}
Grade C count: {N}
Grade D count: {N}
Overall:
- All critical metrics (price, revenue, net_income) Grade A → Overall A
- ≥6 of 10 key metrics Grade A or B → Overall B
- ≥4 of 10 key metrics Grade A, B, or C → Overall C
- Otherwise → Overall D (add warning banner)
Translate to Data Confidence Indicator text:
- Grade A:
Data Confidence: A — All key metrics independently verified - Grade B:
Data Confidence: B — {N} of 10 key metrics cross-referenced - Grade C:
Data Confidence: C — Limited source verification. Review with caution. - Grade D:
Data Confidence: D — ⚠️ Insufficient verified data
Step 8.3 — Section-by-Section Population
Populate each section of html-template.md with data from analysis-result.json.
JSON field → HTML placeholder mapping:
| analysis-result.json field | HTML Section | Placeholder |
|---|---|---|
ticker |
Section 1 | {TICKER} |
company_name |
Section 1 | {COMPANY_NAME} |
exchange |
Section 1 | {EXCHANGE} |
price_at_analysis |
Section 1, 3 | {CURRENT_PRICE} |
price_day_change |
Section 1 | {DAY_CHANGE} |
price_day_change_pct |
Section 1 | {DAY_CHANGE_PCT} |
data_mode |
Section 1 | badge class |
analysis_date |
Section 1 | {ANALYSIS_DATE} |
key_metrics.market_cap |
Section 3 | {MARKET_CAP} |
key_metrics.pe_ratio |
Section 3 | {PE_RATIO} |
key_metrics.ev_ebitda |
Section 3 | {EV_EBITDA} |
key_metrics.fcf_yield |
Section 3 | {FCF_YIELD} |
key_metrics.revenue_growth_yoy |
Section 3 | {REV_GROWTH} |
key_metrics.operating_margin |
Section 3 | {OP_MARGIN} |
scenarios.bull.* |
Section 2 | bull card values |
scenarios.base.* |
Section 2 | base card values |
scenarios.bear.* |
Section 2 | bear card values |
rr_score |
Section 2 | R/R badge |
verdict |
Section 2 | verdict badge |
sections.variant_view_q1 |
Section 4 | Q1 text |
sections.variant_view_q2 |
Section 4 | Q2 text |
sections.variant_view_q3 |
Section 4 | Q3 text |
sections.precision_risks |
Section 4 | risk table rows |
sections.valuation_metrics |
Section 5 | valuation table |
sections.sotp |
Section 5 | SOTP section |
sections.dcf_analysis |
Section 5 | DCF subsection (after SOTP) |
valuation_bridge (top-level) |
Section 5b | {VALUATION_BRIDGE_SECTION} (4 anchors + weighted fair value + reconciliation paragraph) |
sections.macro_context |
Section 4/6 | Macro Environment section |
sections.peer_comparison |
Section 6 | peer table rows |
output/runs/{run_id}/peers/*.json minimum collection_timestamp |
Section 6 | {PEER_COLLECTED_AT_MIN} |
output/runs/{run_id}/peers/*.json maximum collection_timestamp |
Section 6 | {PEER_COLLECTED_AT_MAX} |
sections.analyst_coverage |
Section 7 | analyst data |
historical_prices |
Section 8 | Chart 1 data array |
income_statements |
Section 8, 9 | Charts 2/3, quarterly table |
sections.qoe_summary |
Section 9 | QoE section |
sections.portfolio_strategy |
Section 10 | strategy text |
sections.what_would_make_me_wrong |
Section 10 | WWMMW list |
upcoming_catalysts |
Section 10 | catalyst table |
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.
- 10d ago First seen · 304 lines · 0 tokens per session scan A cbdde499cf79
dashboard-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 3,442 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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