pm-context-system

pm-context-system is a skill for Claude Code from Abhillashjadhav/AI-PM-essential-skills. It costs 198 tokens per session (996 once invoked), scanned A, original, MIT.

A project memory system that records important decisions and facts as the work progresses. It stores approved notes in a context folder so later sessions can find and maintain them.

In plain words
What is it for?
Logging decisions, stakeholder details, and meaningful project changes in one line, then organizing and pruning those notes over time.
Why use it?
It reduces the chance that useful project knowledge will be forgotten or become scattered across conversations. It asks for approval before writing a memory entry.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions CLAUDE.md; mentions Claude Code.

Part of the pm-tactical plugin — 5 skills, 3 agents shipped together

Good fit Logging decisions, stakeholder details, and meaningful project changes in one line, then organizing and pruning those notes over time.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/abhillashjadhav/ai-pm-essential-skills/pm-context-system
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 Abhillashjadhav/AI-PM-essential-skills --skill pm-context-system
Clone the repo
git clone --depth 1 https://github.com/Abhillashjadhav/AI-PM-essential-skills

Made for: Claude Code.

Or install pm-tactical, the plugin that ships this one along with the rest of its 5 skills, 3 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 pm-context-system

README.md
[![agentmods](https://agentmods.dev/badge/skills/abhillashjadhav/ai-pm-essential-skills/pm-context-system/github.svg)](https://agentmods.dev/skills/abhillashjadhav/ai-pm-essential-skills/pm-context-system)
Your own site
<a href="https://agentmods.dev/skills/abhillashjadhav/ai-pm-essential-skills/pm-context-system"><img src="https://agentmods.dev/badge/skills/abhillashjadhav/ai-pm-essential-skills/pm-context-system/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 pm-context-system

Your own site · 80×15
<a href="https://agentmods.dev/skills/abhillashjadhav/ai-pm-essential-skills/pm-context-system"><img src="https://agentmods.dev/badge/skills/abhillashjadhav/ai-pm-essential-skills/pm-context-system.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 198 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 996 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 $0.00198 $0.00996
Opus 5 $0.00099 $0.00498
Sonnet 5 $0.00040 $0.00199
Haiku 4.5 $0.00020 $0.00100

Measured 11d ago against content hash 86954e332ae9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

pm-context-system 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 11d 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.

pm-tactical/skills/pm-context-system/SKILL.md · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PM Context System

A maintained memory structure, not a filing cabinet. Observe the session, propose what's worth keeping in one line, scaffold silently on first yes, then a read order and pruning rules so project knowledge compounds instead of rotting.

Step 1 — Observe and propose (no interview)

Don't front-load an interview. Instead, watch the session as it unfolds. The moment a decision gets made, a stakeholder fact surfaces, or project state changes in a way worth remembering, propose exactly one line:

Log to memory: "<decision or fact + why>" — yes/edit/skip
  • yes → write it (scaffolding context/ silently first if it doesn't exist yet — see Step 2).
  • edit → take the user's correction, then write.
  • skip → drop it, don't ask again about that same fact.

Never write anything without one of these three responses. Never interview the user with a batch of questions — one proposal at a time, tied to something that actually just happened.

Step 2 — Scaffold (silent, triggered by first yes)

If context/ doesn't exist in the project root yet, create it silently the first time a proposal is approved — no announcement, no empty templates shown up front:

context/
├── INDEX.md         ← read-order rules + one-line summary of each file
├── STAKEHOLDERS.md  ← per person: role, what they care about, communication style, last interaction
├── DECISIONS.md     ← append-only: date, decision, why, alternatives rejected
└── STATE.md         ← current project status: active work, blockers, next milestones

Write the approved entry into whichever file it belongs in. Add a pointer in the project's CLAUDE.md: "At session start, read context/INDEX.md first."

Step 3 — Session-start read order

  1. INDEX.md (cheap, routes everything)
  2. STATE.md (what's live right now)
  3. STAKEHOLDERS.md / DECISIONS.md only when the task touches a person or reopens a past decision — progressive disclosure, don't bulk-load.

Step 4 — Session-end catch-all sweep

Real-time proposals (Step 1) cover most of what's worth logging as it happens. Before the session ends (or when the user says "update context"), do one final sweep for anything not already proposed and answered — propose it the same one-line way, never silently write:

  • STATE.md: what changed, what's newly blocked/unblocked
  • DECISIONS.md: any decision made this session not already logged (date + why + rejected alternatives)
  • STAKEHOLDERS.md: only if new information about a person surfaced and wasn't already logged User approves each, then write.

Read the full file on GitHub · 65 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. 11d ago First seen · 65 lines · 198 tokens per session scan A 86954e332ae9

Subscribe to this mod's changes

pm-context-system is a skill published in the GitHub repository Abhillashjadhav/AI-PM-essential-skills (3 stars, last pushed 10d ago), licensed MIT. It adds 198 tokens to every session and 996 once invoked, about $0.0010 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.