Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add jamditis/claude-skills-journalism/plugin install autocontextWrote 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.
[](https://agentmods.dev/commands/jamditis/claude-skills-journalism/init)<a href="https://agentmods.dev/commands/jamditis/claude-skills-journalism/init"><img src="https://agentmods.dev/badge/commands/jamditis/claude-skills-journalism/init.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00013 | $0.01337 |
| Opus 5 | $0.00006 | $0.00668 |
| Sonnet 5 | $0.00003 | $0.00267 |
| Haiku 4.5 | $0.00001 | $0.00134 |
Grade A, and why
init 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Initialize the autocontext knowledge directory in the current project. Use AskUserQuestion for setup decisions.
Pre-initialization check
First, the script checks if .autocontext/ already exists in the project root. If it does, you'll be informed and asked:
Question: This project already has autocontext initialized. Reinitialize?
Options:
- Yes, set up fresh configuration (existing lessons are NOT deleted)
- No, exit and use current setup
If you choose to reinitialize, existing lessons in .autocontext/lessons.json will be preserved but all config files will be reset.
Setup questions
Step 1: Seed from CLAUDE.md (if applicable)
If a CLAUDE.md file exists in the project root:
Question: This project has a CLAUDE.md. Seed initial lessons from it?
Options:
- Yes, extract and let me review each one, parses CLAUDE.md and shows each extracted lesson for approval
- Yes, extract automatically, extracts all lessons without review
- No, start fresh, begins with empty lessons
This helps bootstrap project knowledge from existing documentation.
Step 2: Cross-developer sharing
Question: Will other developers use Claude Code on this repo?
Options:
- Yes, set up cross-developer sharing, enables the union merge driver for collaborative lesson management
- No, just me, single-developer setup, simpler merge strategy
Cross-developer sharing allows multiple Claude instances to work on the same lessons.json without conflicts.
Step 3: Performance baselines
Question: Track test/build performance baselines?
Options:
- Yes, initialize baseline tracking for test and build performance
- No, skip baseline tracking
Performance baselines help detect regressions in test suite and build times over time.
Directory structure creation
The script will create the following structure in .autocontext/:
.autocontext/
├── config.json # Project configuration (shared)
├── config.local.json # Local developer identity
├── lessons.json # Accumulated lessons (git-tracked)
├── playbook.md # Curated lesson playbook (auto-generated)
├── .gitignore # Ignore cache and local files
├── .gitattributes # (if sharing enabled) Configure merge driver
├── cache/ # Temporary files (not git-tracked)
│ ├── pending-lessons.json # (if ask_before_persist) Awaiting approval
│ └── curated-pending.json # From /autocontext:review sessions
└── archive/ # Tombstoned lessons (git-tracked)
└── superseded.json # Deleted lessons for reference
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.
- 7d ago First seen · 143 lines · 13 tokens per session scan A 2adbbaaa7954
init is a command published in the GitHub repository jamditis/claude-skills-journalism (386 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 1,337 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
setup-context
Set up your Skill Memory — a pm-context.md every skill reads so outputs come back tailored to you.
reflect
Capture learnings from the current conversation through guided reflection.
continuity
Read and update working memory — maintain context across sessions via CONTINUITY.md.
claude-recall
Update project context using the local LLM (Qwen2.5 0.5B).
dossier
Force load of Dossier vault profile (and inbox check) before processing the rest of the user's request.
analyze-writing
Analyze academic writing quality of the current draft. Checks for passive voice overuse, weak openings, hedging balance, readability, sentence length variation, and word repetitions. Produces a writing quality report with specific improvement suggestions per section.