A command that assembles a privacy-cleaned report about a John run, including its process scorecard, file manifest, outcome summary, and possible lessons. John appears to be a project workflow system; the input does not explain it further.

Use it when a run finishes, a milestone ships, or someone asks how the run went. It requires a John workspace initialized with /john:init.

It turns the records from a completed run into a shareable report and leaves behind files that help others audit how the run was performed.

report — Command for coding agents by kitchen-engineer42: A command that assembles a privacy-cleaned report about a…

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 commands/kitchen-engineer42/joharnessburg/report

Clone the repo

git clone --depth 1 https://github.com/kitchen-engineer42/joharnessburg

Or install john, the plugin that ships this one along with the rest of its 28 skills, 5 commands, 5 agents, 3 hooks.

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/kitchen-engineer42/joharnessburg/report.svg)](https://agentmods.dev/commands/kitchen-engineer42/joharnessburg/report)

Your own site

<a href="https://agentmods.dev/commands/kitchen-engineer42/joharnessburg/report"><img src="https://agentmods.dev/badge/commands/kitchen-engineer42/joharnessburg/report.svg" alt="Measured on agentmods" height="20"></a>

Per session 86 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 605 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.

Model	Per session	Once invoked
Fable 5	$0.00086	$0.00605
Opus 5	$0.00043	$0.00302
Sonnet 5	$0.00017	$0.00121
Haiku 4.5	$0.00009	$0.00060

Measured 5d ago against content hash b4e7429a0f00, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

report 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.

plugins/joharnessburg/commands/report.md · 28 lines

What it actually says

When this command fires:

Run the process scorecard via Bash (add --applied-metadata ${CLAUDE_PLUGIN_ROOT}/.applied-metadata.json when running under an applied template — that file sits at the merged plugin's root):
```
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/process_scorecard.py"
```
On success: false ("No .john/ directory"), tell the user there's no workspace to report on — /john:init first.

Then emit the auditor manifests (idempotent, zero-token; same --applied-metadata note as above):
```
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/emit_manifests.py" --applied-metadata "${CLAUDE_PLUGIN_ROOT}/.applied-metadata.json"
```
This writes <project>/.john/PROVENANCE.json (run identity — John version, template name+version, corpus inputs, observed phases, run window) and SELF_EVAL_MANIFEST.json (how to re-run the scorecard, where reports live), so the finished run is legible to an external auditor and John's own evolution tooling without reading app code. A missing .applied-metadata.json is fine — a vanilla run emits both with template fields null. (Where a produced app wrote its results is template-defined; John core does not emit that manifest.)
Assemble the report at <project>/.john/reports/<YYYY-MM-DD>-run-report.md, following the format in the skill-evolution skill's references/run-report-format.md (1 page: manifest, scorecard highlights, outcome summary, candidate lessons, deviations). Create the reports/ directory if missing. The scorecard JSON is the evidence backbone; your judgment supplies the outcome summary and the lesson selection — pick the few lessons whose scope_guess is template or core and whose evidence held up.
Walk the scrub-and-generalize checklist (bottom of the format reference) over the draft — the report is built to LEAVE this project, so it must carry no corpus content, client identifiers, or local filesystem paths. Restate any lesson that fails the check so it would hold for the next corpus of the domain.
Show the user the report path and the highlights. Remind them: sharing is manual and theirs — typically to the template's owner as evolution evidence. Nothing is ever transmitted automatically.

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.

5d ago First seen · 28 lines · 86 tokens per session scan A b4e7429a0f00

Subscribe to this mod's changes

report is a command published in the GitHub repository kitchen-engineer42/joharnessburg (9 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 605 once invoked, about $0.0004 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.

Planning Writing and docs ai-agents anthropic claude claude-code claude-code-plugin knowledge-engineering

report

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

What it actually says

What this file has done since we first saw it

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