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.
git clone --depth 1 https://github.com/aborroy/aiup-alfrescoWrote 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/aborroy/aiup-alfresco/metadata-extractor)<a href="https://agentmods.dev/commands/aborroy/aiup-alfresco/metadata-extractor"><img src="https://agentmods.dev/badge/commands/aborroy/aiup-alfresco/metadata-extractor.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 | $0.00042 | $0.02030 |
| Opus 5 | $0.00021 | $0.01015 |
| Sonnet 5 | $0.00008 | $0.00406 |
| Haiku 4.5 | $0.00004 | $0.00203 |
Grade A, and why
metadata-extractor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/metadata-extractor — Metadata Extractor Generator
In-Process SDK only — metadata extractors deploy inside the ACS JVM as part of the Platform JAR. They map values found in a file's content into node properties at upload time — distinct from renditions/transforms (
/transforms), which convert content into other content.
Generate a custom metadata extractor (and optional embedder) from requirements.
Input
Read REQUIREMENTS.md to identify metadata extraction requirements:
-
Resolve the Platform JAR project's
Root pathfrom Section 2 (Project Architecture).- If Section 2 contains no
Platform JARproject, stop and explain that/metadata-extractoronly applies to the in-process Platform JAR project.
- If Section 2 contains no
-
Read the "Metadata extraction requirements" sub-section (Section 7 Behaviour Requirements or a dedicated section).
- If none are present, stop and ask the user to run
/requirementsfirst (or provide a description as$ARGUMENTS). - Check coverage first: ACS routes extraction for common formats (Office, PDF, images, audio/video) through the Transform Service's Tika engine. Only scaffold a custom in-process extractor for a bespoke format or a custom source→property mapping that the standard extractors do not provide.
- If none are present, stop and ask the user to run
-
From Section 2, derive:
{platform-project-root}—.for Platform JAR only mode;{name}-platform/for Mixed mode{module-id}— the Platform JAR artifactId (bare artifact ID, e.g.my-extension). Read from<artifactId>in the platformpom.xmlor derive as{platform-artifactId}from Section 2. Never use the fullmodule.idproperty value as the directory name.{java-package}— the Java package declared in Section 2{package-path}—{java-package}with dots replaced by slashes (resource path){prefix}— the namespace prefix declared in Section 5 (Content Model Requirements)
-
Derive from extraction requirements:
{Name}— PascalCase extractor name (e.g.Contract,Invoice){sourceMimetype}— the MIME type(s) the extractor supports- The source→target mapping: each raw key in the file → a content-model property QName
(e.g.
vendor→{prefix}:vendor)
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.
- 6d ago First seen · 201 lines · 42 tokens per session scan A 1529524d9895
metadata-extractor is a command published in the GitHub repository aborroy/aiup-alfresco (13 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 42 tokens to every session and 2,030 once invoked, about $0.0002 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
earnings-preview
Earnings preview presentation — 4-6 slide deck with consensus estimates, historical surprises, forward catalysts.
audit-xls
Audit an Excel workbook — formula errors, hardcoded cells, calculation arc cross-validation.
generate-pdf-document
Specify a generated PDF that survives variable content, with fonts, page breaks, and accessibility handled.
test-report
Write a point-in-time test report as Markdown in the user's repository. Use when invoked as /document-design-system:test-report. Produce designed HTML or PDF only when asked.
browse
Generate a single-file markdown browser HTML — tree sidebar + marked.js render. Scans project docs/ + /.claude/{plans,projects} by default.
convert
Convert a file to Markdown using nutritious.md.