A report-writing step that combines existing company research, stock valuation results, and the assumptions behind them into an investment report. It reads saved material rather than performing new web searches or API calls.

Use it to create a structured investment report for a stock ticker after the research and valuation files already exist.

It turns separate research and valuation outputs into one consistent document with a verdict, risks, assumptions, and possible changes.

report — Skill for Claude Code by cimomo

Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code

/plugin marketplace add cimomo/intrinsic

Claude Code

/plugin install intrinsic

Made for: Claude Code.

Or install intrinsic, the plugin that ships this one along with the rest of its 6 skills.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/cimomo/intrinsic/report.svg)](https://agentmods.dev/skills/cimomo/intrinsic/report)

Your own site

<a href="https://agentmods.dev/skills/cimomo/intrinsic/report"><img src="https://agentmods.dev/badge/skills/cimomo/intrinsic/report.svg" alt="Measured on agentmods" height="20"></a>

Per session 12 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,857 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00012	$0.01857
Opus 5	$0.00006	$0.00928
Sonnet 5	$0.00002	$0.00371
Haiku 4.5	$0.00001	$0.00186

Measured 7d ago against content hash 560bae498743, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

report 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 7d 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.

skills/report/SKILL.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Generate a comprehensive investment report for ticker symbol $ARGUMENTS by synthesizing qualitative research, quantitative valuation, and assumption metadata into an opinionated verdict.

This skill does NOT perform web searches or API calls — it synthesizes existing files only.

Python Environment

When running Python code, set PYTHONPATH so stock_analyzer is importable:

PYTHONPATH="${CLAUDE_PLUGIN_ROOT:-.}" python3 -c "from stock_analyzer import ..."

Output Template

The report MUST follow this structure:

# {Company} ({TICKER}) — Investment Report
**Date:** YYYY-MM-DD

## Verdict
**ASSESSMENT** | Fair value: $XXX (range: $XXX-$XXX) | Current: $XXX | Upside: X.X%
Confidence: High/Medium/Low | Signals: Growth X (Y), Moat X/Y, Margin X, Capital X

## The Investment Case
[one paragraph]

## Alignment Check
[signal vs assumption, key risks vs valuation structure, key debate vs assumptions]

## What You're Paying For
[reverse DCF context + manual overrides as specific bets]

## Key Assumption Vulnerability
[the one or two assumptions that flip the assessment]

## What Would Change This
[specific triggers with timeframes]

## Prior Analysis (if available)
[omit if no prior analysis exists]

Steps:

1. Load and Validate Inputs

Load the most recent research_*.md from data/$ARGUMENTS/
Load the most recent valuation_*.md from data/$ARGUMENTS/
Load assumptions.json from data/$ARGUMENTS/ including _manual_overrides via StockManager.load_manual_overrides(). If assumptions.json doesn't exist or has no _manual_overrides: note "No calibration metadata available" and base the "What You're Paying For" section on valuation output only.
If research is missing: Tell the user to run /research $ARGUMENTS first, then stop
If valuation is missing: Tell the user to run /value $ARGUMENTS first, then stop
Freshness validation: Compare dates of research and valuation files. If they differ by more than 1 day, warn: "Research is from {date1}, valuation from {date2} — they may reflect different data. Consider re-running the older one." Do not stop.
Check for prior analysis_*.md files for the Prior Analysis section
Display: "Based on research_{date}.md, valuation_{date}.md, assumptions.json"

Read the full file on GitHub · 137 lines

Changes

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.

7d ago First seen · 137 lines · 12 tokens per session scan A 560bae498743

Subscribe to this mod's changes

report is a skill published in the GitHub repository cimomo/intrinsic (4 stars, last pushed 4mo ago), licensed MIT. It adds 12 tokens to every session and 1,857 once invoked, about $0.0001 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 2026-08-31.

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