session-planning

session-planning is a skill for Claude Code from strikersam/autonomous-ai-agency. It costs 18 tokens per session (1,434 once invoked), scanned C, original, MIT.

A planning workflow that requires an AI coding agent to break down a non-trivial task before changing code. It includes project orientation, skill selection, task understanding, a draft pull request, and user confirmation.

In plain words
What is it for?
Use it to inspect project guidance and current work, decompose issues, load relevant skills, prepare a draft pull request, and request confirmation.
Why use it?
It creates a documented sequence for understanding the repository and agreeing on the work before implementation begins.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions Claude Code.

Good fit Use it to inspect project guidance and current work, decompose issues, load relevant skills, prepare a draft pull request, and request confirmation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/strikersam/autonomous-ai-agency/session-planning
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 strikersam/autonomous-ai-agency --skill session-planning
Clone the repo
git clone --depth 1 https://github.com/strikersam/autonomous-ai-agency

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 session-planning

README.md
[![agentmods](https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/session-planning/github.svg)](https://agentmods.dev/skills/strikersam/autonomous-ai-agency/session-planning)
Your own site
<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/session-planning"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/session-planning/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 session-planning

Your own site · 80×15
<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/session-planning"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/session-planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,434 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 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 $0.00018 $0.01434
Opus 5 $0.00009 $0.00717
Sonnet 5 $0.00004 $0.00287
Haiku 4.5 $0.00002 $0.00143

Measured 8d ago against content hash 7f8685756f3c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade C, and why

session-planning scanned grade C with 2 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 8d 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

cat .claude/state/active-tasks.md # what's already in flight

Enumerates other installed skillsmediumAgent snooping

Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.

ls .claude/skills/ # see all available skills
.claude/skills/session-planning/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: session-planning — Mandatory Planning Workflow for All AI Agents

When to use: At the start of EVERY non-trivial agentic session, before writing any code. This skill is universal — it works with Claude Code, Codex, Cursor, Aider, and any other AI tool that reads AGENTS.md or CLAUDE.md.


The 10-Step Workflow

Run these steps in order. Do not skip steps 6 (draft PR) or 7 (user confirmation).

Step 1 — Orient (free)

cat AGENTS.md                                    # cross-tool ground truth
cat CLAUDE.md                                    # project-specific rules
cat graphify-out/GRAPH_REPORT.md                 # codebase map (no token cost)
cat .claude/state/active-tasks.md               # what's already in flight
cat docs/changelog.md | head -40                # what recently changed

Step 2 — Understand the Task

  • If from a GitHub issue: read the issue body, comments, linked PRs
  • If from a user message: restate the task in one sentence to confirm understanding
  • If resuming: read .claude/state/NEXT_ACTION.md and active-tasks.md

Step 3 — Load Relevant Skills

ls .claude/skills/                               # see all available skills
# Load skills matching the task type:
# Multi-file change       → implementation-planner
# Tests needed            → test-first-executor
# Auth/key/agent-tools    → risky-module-review
# Pre-merge review        → council-review
# Adding deps             → dependency-audit
# Codebase exploration    → graphify
# Cross-harness routing   → ecc-harness-patterns

Step 4 — Research (if novel task)

  • If the task involves techniques not in the codebase, search OSS reference projects
  • Use web search or GitHub MCP to read relevant repos
  • Cite sources in the plan

Step 5 — Write the Plan

Use the implementation-planner skill or write directly:

## Plan: <task name>

**Goal:** one sentence

**Files to change:**
- `path/to/file.py` — what changes and why
- `path/to/other.py` — what changes and why

**Steps:**
1. Write tests first (test-first-executor)
2. Implement step A
3. Implement step B
4. Run pytest -x
5. Update changelog
6. Update active-tasks.md

**Risks:** list risky modules requiring risky-module-review

**Acceptance criteria:** how to verify it works

Read the full file on GitHub · 172 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. 8d ago First seen · 172 lines · 18 tokens per session scan C 7f8685756f3c

Subscribe to this mod's changes

session-planning is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 1,434 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 2 findings (reads agent configuration directories, enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.