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 agentii-ai/agentii-investment-intelligence --skill 3-statementgit clone --depth 1 https://github.com/agentii-ai/agentii-investment-intelligenceWrote 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/agentii-ai/agentii-investment-intelligence/3-statement)<a href="https://agentmods.dev/skills/agentii-ai/agentii-investment-intelligence/3-statement"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/3-statement/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/agentii-ai/agentii-investment-intelligence/3-statement"><img src="https://agentmods.dev/badge/skills/agentii-ai/agentii-investment-intelligence/3-statement.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 | $0.00046 | $0.01938 |
| Opus 5 | $0.00023 | $0.00969 |
| Sonnet 5 | $0.00009 | $0.00388 |
| Haiku 4.5 | $0.00005 | $0.00194 |
Grade A, and why
3-statement 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 4d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preflight
Run the canonical pre-flight sequence — MCP health probe, ticker resolution, workspace style.md override, memory load, and coverage check. See contracts/preflight.md.
Include the X-Agentii-Trace header on every tool call per contracts/x-agentii-trace-header.md.
Triggers
- analyze 3 statement model
- run 3 statement model analysis
- produce 3 statement model report
- 3 statement model breakdown
- 3 statement model deep dive
- build a 3 statement model
- assess 3 statement model
- quantify 3 statement model
- compare 3 statement model across peers
- review 3 statement model for
- generate 3 statement model on
- 3 statement model for investment decision
Defaults
| Parameter | Default | Notes |
|---|---|---|
| lookback_years | 3 | Historical data window |
| include_peers | false | Whether to surface a peer comparison block |
Methodology
Retrieval Scope
This skill performs unstructured document search at scale across SEC filings and earnings call transcripts (10-K, 10-Q, 8-K). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale.
Retrieval Strategy
See contracts/retrieval.md for the canonical decision tree; skill-specific retrieval detail is in references/methodology.md.
Temporal Scope
Default: 12 fiscal quarters (max 20). Financial modeling: trailing 12 quarters (3 fiscal years) for long-range projection inputs.
Tool Allowlist
See frontmatter allowed_tools.
Protocol
Step-by-step execution detail is in references/methodology.md.
Deliverable Chain
Inputs → Build → Validate → Output → Next
- Inputs: resolved ticker + 3 years of
search_xbrl_facts(Income Statement, Balance Sheet, Cash Flow) +get_statement_structurefor presentation tree. - Build: write a self-contained Python script using
openpyxlthat creates the 3-statement workbook per## Output Structure. Execute viaBash: python3 script.py. Verify the.xlsxexists at the output path. Ifimport openpyxlfails, fall back to.mdsummary withdata_availability: degraded(seecontracts/office-tooling.md). - Validate: run LibreOffice recalc; audit cross-statement checks (BS balances, CF ties to BS, IS flows to CF) per
## Validation Gates. - Output: write the artifact path per
## Output File. - Next: append to
agentii.md; hand off to a downstream pitch/review skill if requested.
What ships with it
8 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.
- 4d ago Changed e135a3e963b1
- 10d ago First seen · 138 lines · 46 tokens per session scan A 352f2094dadd
3-statement is a skill published in the GitHub repository agentii-ai/agentii-investment-intelligence (203 stars, last pushed today), licensed Apache-2.0. It adds 46 tokens to every session and 1,938 once invoked, about $0.0002 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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