opportunity-scorer

opportunity-scorer is a skill for Claude Code from o2alexanderfedin/strategic-research-automation-template. It costs 0 tokens per session (3,505 once invoked), scanned A, original, MIT.

A scoring method for comparing business or product opportunities on a 0–100 scale using weighted criteria from a configuration file. It extracts evidence from research and applies the configured scoring rubric.

In plain words
What is it for?
Use it to score, rank, compare, or make go/no-go recommendations about opportunities using dimensions such as market potential and other configured criteria.
Why use it?
It turns scattered research into comparable scores and explains whether an opportunity is a strong go, go, conditional go, or no go.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: positional $N argument.

Good fit Use it to score, rank, compare, or make go/no-go recommendations about opportunities using dimensions such as market potential and other configured criteria.

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Install with agentmods
npx agentmods add skills/o2alexanderfedin/strategic-research-automation-template/opportunity-scorer
Install

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.

Any agent
npx skills add o2alexanderfedin/strategic-research-automation-template --skill opportunity-scorer
Clone the repo
git clone --depth 1 https://github.com/o2alexanderfedin/strategic-research-automation-template

Made for: Claude Code.

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.

agentmods badge for opportunity-scorer

README.md
[![agentmods](https://agentmods.dev/badge/skills/o2alexanderfedin/strategic-research-automation-template/opportunity-scorer/github.svg)](https://agentmods.dev/skills/o2alexanderfedin/strategic-research-automation-template/opportunity-scorer)
Your own site
<a href="https://agentmods.dev/skills/o2alexanderfedin/strategic-research-automation-template/opportunity-scorer"><img src="https://agentmods.dev/badge/skills/o2alexanderfedin/strategic-research-automation-template/opportunity-scorer/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.

agentmods 80×15 button for opportunity-scorer

Your own site · 80×15
<a href="https://agentmods.dev/skills/o2alexanderfedin/strategic-research-automation-template/opportunity-scorer"><img src="https://agentmods.dev/badge/skills/o2alexanderfedin/strategic-research-automation-template/opportunity-scorer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,505 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.03505
Opus 5 $0.00000 $0.01752
Sonnet 5 $0.00000 $0.00701
Haiku 4.5 $0.00000 $0.00350

Measured 12d ago against content hash b43f9e425dc5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

opportunity-scorer 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 12d 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.

.claude/skills/opportunity-scorer/SKILL.md · 475 lines

How it starts

The opening of the file, as written. The whole thing — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.



name: "opportunity-scorer" description: | Calculates quantitative opportunity scores (0-100) using multi-dimensional rubrics from configuration. Activates when: scoring opportunities, calculating weighted scores, applying scoring rubrics, generating go/no-go recommendations, comparing opportunity scores, or ranking multiple opportunities. Reads research findings, extracts evidence, applies scoring criteria, and produces justified scores with threshold-based recommendations (STRONG GO, GO, CONDITIONAL GO, NO GO). allowed-tools:

  • Read
  • Write
  • Grep
  • Glob


Opportunity Scorer Skill

Role

You are the Opportunity Scorer, responsible for calculating quantitative opportunity scores (0-100) using multi-dimensional scoring rubrics defined in configuration.

Core Responsibilities

1. Rubric Loading and Parsing

Configuration File: config/scoring-rubric.yml

Rubric Structure:

scoring:
  market_opportunity:                # Dimension name
    weight: 0.25                     # Dimension weight (0-1)
    description: "Market size, growth, pain points"
    criteria:                         # Sub-criteria
      - name: "tam_sam_som"
        weight: 0.4                   # Sub-criterion weight (0-1)
        description: "TAM/SAM/SOM sizing"
      - name: "growth_rate"
        weight: 0.3
        description: "Market CAGR"
      - name: "customer_pain"
        weight: 0.3
        description: "Pain severity"
  # ... [more dimensions]

thresholds:
  strong_go: 80                       # ≥80: STRONG GO
  go: 65                              # 65-79: GO
  conditional_go: 50                  # 50-64: CONDITIONAL GO
  no_go: 50                           # <50: NO GO

Loading Process:

  1. Use Read to load config/scoring-rubric.yml
  2. Parse YAML structure
  3. Extract dimensions, weights, criteria
  4. Extract threshold values

2. Evidence Extraction

Objective: Extract scoring-relevant information from research files

Read the full file on GitHub · 475 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.

  1. 12d ago First seen · 475 lines · 0 tokens per session scan A b43f9e425dc5

Subscribe to this mod's changes

opportunity-scorer is a skill published in the GitHub repository o2alexanderfedin/strategic-research-automation-template (19 stars, last pushed 9mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,505 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.