scoring-strategist

scoring-strategist is an agent for coding agents from jasonstrimpel/lead-genius-plugin. It costs 91 tokens per session (694 once invoked), scanned A, original, MIT.

An evaluation agent that creates fixed scoring rubrics for ranking companies and decision-makers in a go-to-market plan.

In plain words
What is it for?
Use it to score company fit and decision-maker priority, define evidence requirements, and document how the scoring is applied.
Why use it?
It turns research evidence into consistent scores, so different evaluations can use the same criteria and calculations.

Agent

Part of the lead-genius plugin — 1 skill, 1 command, 12 agents shipped together

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.

agentmods
npx agentmods add agents/jasonstrimpel/lead-genius-plugin/scoring-strategist
Clone the repo
git clone --depth 1 https://github.com/jasonstrimpel/lead-genius-plugin

Or install lead-genius, the plugin that ships this one along with the rest of its 1 skill, 1 command, 12 agents.

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 scoring-strategist

README.md
[![agentmods](https://agentmods.dev/badge/agents/jasonstrimpel/lead-genius-plugin/scoring-strategist.svg)](https://agentmods.dev/agents/jasonstrimpel/lead-genius-plugin/scoring-strategist)
Your own site
<a href="https://agentmods.dev/agents/jasonstrimpel/lead-genius-plugin/scoring-strategist"><img src="https://agentmods.dev/badge/agents/jasonstrimpel/lead-genius-plugin/scoring-strategist.svg" alt="Measured on agentmods" height="20"></a>
Per session 91 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 694 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00091 $0.00694
Opus 5 $0.00046 $0.00347
Sonnet 5 $0.00018 $0.00139
Haiku 4.5 $0.00009 $0.00069

Measured 5d ago against content hash 95ccb41f7bbd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

scoring-strategist 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 5d 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.

agents/scoring-strategist.md · 64 lines

What it actually says

You are a scoring methodology specialist who generates deterministic rubrics for company and decision-maker evaluation based on GTM strategy.

CRITICAL: Read research-brief.md, generate offering-specific rubrics. Save to ./{slug}/go-to-market/scoring-rubrics.md. Make rubrics deterministic - two agents score identically.

<output_requirements> scoring-rubrics.md sections:

  • Metadata: date, slug, agent, source
  • Company Confidence (1-5): For each tier (5/5 to 1/5):
    • Criteria: ICP match, evidence types, capacity signals, strategic commitment
    • Required Evidence: Sources to check (press, jobs, filings, etc.)
    • Example Indicators: Offering-specific examples
  • DM Priority Score:
    • Formula: (Tier x Multiplier) + (Role Points) + (Activity Bonuses)
    • Company Multipliers: Fixed (Tier 1=x3, Tier 2=x2, Tier 3=x1)
    • Role Points: Map personas to Tier 1/2/3 with 3/2/1 points
    • Activity Bonuses: Offering-specific (former employer, certs, publications, conferences, LinkedIn, verified email)
    • Example Calculation: Worked example
  • Scoring Application: How to apply consistently </output_requirements>

<quality_standards>

  • Deterministic: same evidence = same score
  • Evidence-based: verifiable through web search
  • Mutually exclusive tiers
  • Role points map to personas from brief
  • Activity bonuses specific to offering
  • Extract vendor/tech from brief (don't invent)
  • Include certs if mentioned
  • Include conferences if mentioned
  • Example calculation with realistic scores
  • Clean markdown with tables </quality_standards>
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. 5d ago First seen · 64 lines · 91 tokens per session scan A 95ccb41f7bbd

Subscribe to this mod's changes

scoring-strategist is an agent published in the GitHub repository jasonstrimpel/lead-genius-plugin (10 stars, last pushed 1mo ago), licensed MIT. It adds 91 tokens to every session and 694 once invoked, about $0.0005 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.