pm-decision-model

pm-decision-model is a skill for Claude Code from ljucask/pureinn-product-development. It costs 101 tokens per session (1,822 once invoked), scanned A, original, MIT.

A helper for documenting one decision table: a matrix showing how different combinations of conditions lead to different results. It is meant for decisions that cannot be described by one simple if-then rule.

In plain words
What is it for?
Use it for pricing matrices, eligibility checks, risk scores, discount tiers, and other decisions with several conditions and possible outcomes.
Why use it?
It keeps complicated business logic in a form people can inspect, discuss, and reference without rerunning the whole business-rules process.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions CLAUDE.md; mentions subagents; names the AskUserQuestion tool.

Part of the pureinn-product-development plugin — 51 skills, 1 command shipped together

Good fit Use it for pricing matrices, eligibility checks, risk scores, discount tiers, and other decisions with several conditions and possible outcomes.

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Install with agentmods
npx agentmods add skills/ljucask/pureinn-product-development/pm-decision-model
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 ljucask/pureinn-product-development --skill pm-decision-model
Clone the repo
git clone --depth 1 https://github.com/ljucask/pureinn-product-development

Made for: Claude Code.

Or install pureinn-product-development, the plugin that ships this one along with the rest of its 51 skills, 1 command.

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.

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README.md
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Your own site
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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.

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Your own site · 80×15
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Per session 101 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,822 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 $0.00101 $0.01822
Opus 5 $0.00051 $0.00911
Sonnet 5 $0.00020 $0.00364
Haiku 4.5 $0.00010 $0.00182

Measured 10d ago against content hash da51f1ea3b84, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

pm-decision-model 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.

skills/pm-decision-model/SKILL.md · 162 lines

How it starts

The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PM - Decision Model (JIT Helper)

Agent mode (--agent)

Supports --agent: runs autonomously in a subagent, drafts the artifact from existing inputs, and returns a short summary + coverage note.

  • No flag → interactive (default); if inputs are heavy, offer agent mode.
  • --agent → obey. First check inputs are complete. Anything missing: do NOT invent it - mark [ASSUMED - what/why] in the output and summary. Never hallucinate to fill a gap.
  • Review required: the artifact contains commitments - after drafting, require the user's review before finalizing; do not close decisions autonomously.

What this skill does

Adds a single decision table (TBL-[DOMAIN]-NN) to domain/decision_models.md (Live Register 3) - without re-running the full pm-business-rules-library. This is the decision-models counterpart to the single-rule helpers: where pm-business-rule-core/critical/governance add one business rule to Register 2, this adds one decision table to Register 3.

A decision table belongs here when:

  • Several input conditions combine to produce different outputs (not a single if/then)
  • The logic is best read as a matrix - rows = condition combinations, columns = inputs + output
  • Examples: discount tiers by customer level + order value + promo, eligibility by age + region + status, risk score by multiple signals, pricing matrix

If the logic is a single condition → one output, it is a business rule, not a table → use pm-business-rule-core / -critical / -governance instead.

When to run: During pm-feature-design when the JIT design reveals multi-condition logic that should be centralized. Or standalone when a decision matrix needs to be formalized before a feature enters build. (pm-business-rule-core routes here when a rule it is adding turns out to have multiple condition combinations.)


Dependencies

Required before running:

  • pm-business-rules-library - domain/decision_models.md must exist (initialized in Phase 4)
  • pm-entity-registry - entity context for scoping the table

Read the full file on GitHub · 162 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. 10d ago First seen · 162 lines · 101 tokens per session scan A da51f1ea3b84

Subscribe to this mod's changes

pm-decision-model is a skill published in the GitHub repository ljucask/pureinn-product-development (2 stars, last pushed today), licensed MIT. It adds 101 tokens to every session and 1,822 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.

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