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.
npx agentmods add skills/ljchang/mecha/updatenpx skills add ljchang/mecha --skill updategit clone --depth 1 https://github.com/ljchang/mechaWhat 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 | $0.00070 | $0.04811 |
| Opus 5 | $0.00035 | $0.02405 |
| Sonnet 5 | $0.00014 | $0.00962 |
| Haiku 4.5 | $0.00007 | $0.00481 |
Grade A, and why
update scanned grade A with 1 finding 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
answers 400, which reads exactly like a server bug and is your curl. Two How it starts
The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Updating everything
There is no single command, and that is the whole problem. "Update" names six independent surfaces on two machines from three repositories, each with its own version line. Every one of them can be stale while the others are current, and none of them complain.
The failure this skill exists to prevent, from 2026-08-15: mecha 0.1.4 was
tagged, pushed, and published to crates.io, and the services were restarted —
and mecha --version still said 0.1.3 afterwards, because nothing had run
cargo install. Four surfaces were stale at once that day: the installed
binaries, mecha-triggers (left out of the restart), the benchmark's musl
binary (eight days old, so a benchmark would have measured old code and
reported it as new), and the factory client.
The one rule
Verify the running thing, never the repo.
A tag proves a commit exists. A green CI run proves it compiles. git log
proves someone wrote it. None of them prove that the bytes executing on this
machine contain it. Ask the process what it is, not the source tree:
mecha --version, ls -l ~/.cargo/bin/, /proc/<pid>/exe.
Three specific confusions worth naming, because each one has actually happened:
- A release is not an install. Tagging and publishing changes crates.io,
not
~/.cargo/bin. - A restart is not a reinstall.
systemctl restartre-executes the same file on disk. Restarting before installing accomplishes nothing. - A debug build is not the one that runs. Both mecha's MCP config and the benchmark point at release paths.
The six surfaces
Work them in this order — later ones depend on earlier ones.
1. Installed binaries (~/.cargo/bin)
From ~/Github/mecha:
cargo install --path mecha-cli --locked --force # mecha
cargo install --path mecha-mail --locked --force # mecha-mail, mecha-google, mecha-outlook
And the graph, from ~/Github/personalized_knowledge_graph — installed with
mecha since 2026-08-16, because ~/.mecha/config.toml runs
~/.cargo/bin/mecha-graph-mcp, not a repo path.
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.
- 2d ago First seen · 371 lines · 70 tokens per session scan A 8b75ae5527d2
update is a skill published in the GitHub repository ljchang/mecha (6 stars, last pushed 2d ago), licensed MIT. It adds 70 tokens to every session and 4,811 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
python-feature-lifecycle
Guidance for package and feature lifecycle in the Agent Framework Python codebase, including stage meanings, feature-stage decorators, feature enums, and how to move APIs from one stage to the next.
build-and-test
How to build and test .NET projects in the Agent Framework repository. Use this when verifying or testing changes.
python-development
Coding standards, conventions, and patterns for developing Python code in the Agent Framework repository. Use this when writing or modifying Python source files in the python/ directory.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
unit-converter
Convert between common units using a multiplication factor. Use when asked to convert miles, kilometers, pounds, or kilograms.