context_product_plan

context_product_plan is a skill for Codex from Seven128/project-tiny-context-harness. It costs 102 tokens per session (847 once invoked), scanned A, original, MIT.

A product-planning guide for projects using Minimal Context Harness, a system for keeping an AI coding project’s context organized. It defines users, goals, scope, rules, flows, and acceptance criteria.

In plain words
What is it for?
Use it when you need a product specification, requirements, user stories, user flows, business rules, or criteria for deciding whether a feature is complete.
Why use it?
It prevents coding work from starting with unclear product decisions or from mixing product requirements with design and implementation details.

Skill for Codex

Written for Codex: installed under .codex/.

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 skills/seven128/project-tiny-context-harness/context_product_plan
Any agent
npx skills add Seven128/project-tiny-context-harness --skill context_product_plan
Clone the repo
git clone --depth 1 https://github.com/Seven128/project-tiny-context-harness

Made for: Codex.

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 context_product_plan

README.md
[![agentmods](https://agentmods.dev/badge/skills/seven128/project-tiny-context-harness/context_product_plan.svg)](https://agentmods.dev/skills/seven128/project-tiny-context-harness/context_product_plan)
Your own site
<a href="https://agentmods.dev/skills/seven128/project-tiny-context-harness/context_product_plan"><img src="https://agentmods.dev/badge/skills/seven128/project-tiny-context-harness/context_product_plan.svg" alt="Measured on agentmods" height="20"></a>
Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 847 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 $0.00102 $0.00847
Opus 5 $0.00051 $0.00424
Sonnet 5 $0.00020 $0.00169
Haiku 4.5 $0.00010 $0.00085

Measured 5d ago against content hash f31e6fbfd5c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

context_product_plan 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.

.codex/skills/context_product_plan/SKILL.md · 43 lines

How it starts

The opening of the file, as written. The whole thing — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Context Product Plan

Ownership

Own product meaning: goals, users, problem, scope/non-goals, business and user-visible rules, user flows, product feedback, success/acceptance meaning and genuine product decisions. This Skill does not own Product Surface placement, visual Design Authority, generated design resources, technical architecture, implementation, verification authority or a Gate.

Project-specific product behavior belongs in project_context/** and may be specialized by <harnessRoot>/skills/product_plan/SKILL.md. Durable conclusions never live only in the Skill output.

When Long-Task is active, it alone owns Source/Contract lifecycle and Final Gate. This Skill may clarify product meaning for the existing Source/Context, but creates no second plan, requirement ledger, stage or acceptance path.

Workflow

  1. Read project_context/global.md, project_context/context.toml, the default area and product owners triggered by the request. Use the default Workflow Contract's bounded high-signal Context search before Context Delta.
  2. Establish target users/actors, problem and desired outcome, scope/non-goals, relevant objects/capabilities, main flow and material alternatives, business/user rules, failure/degraded/recovery expectations, success signals and real decision gaps.
  3. Treat explicit user/product/legal/security/commercial/external constraints as Source. Internally classify each material constraint as Context-covered, requiring Context update, task-local, out of scope or decision-required. Current code reveals implementation; it cannot silently redefine product intent.
  4. Keep conditions and acceptance concrete enough to be observed through the actual product entry. A representative sample cannot satisfy a declared full-population/all-provider/all-interface/all-platform outcome; unresolved scope is decision-required.
  5. Route durable information/action/feedback placement, main-versus-drilldown responsibility, screen ownership or cross-surface IA to context_surface_contract. Provide goals, users, flows, rules and acceptance meaning as inputs; do not compile a Surface Contract here.
  6. Route durable visual identity/tokens/rationale/adopted-target interpretation to context_uiux_design; new resource generation to design-resource-authoring; architecture/engineering design to context_development_engineer.
  7. Decide exactly one Context Delta: none|required. Update the smallest product owner before implementation when goals, scope, business/user rules, flow ownership, acceptance semantics or durable rationale change. Local bugs or implementation drift that preserve meaning are none.
  8. Under the default Workflow Contract, hand implementation to the current Goal and include product conformance in its one current-candidate Contract Conformance. Under Long-Task, project exact non-UI meaning from this product owner into its existing Source/Contract mechanism only—never build a nested Fact ledger or second closure.

Read the full file on GitHub · 43 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. 5d ago First seen · 43 lines · 102 tokens per session scan A f31e6fbfd5c1

Subscribe to this mod's changes

context_product_plan is a skill published in the GitHub repository Seven128/project-tiny-context-harness (3 stars, last pushed yesterday), licensed MIT. It adds 102 tokens to every session and 847 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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