Borrowing it
Nothing to install: this file belongs to DavidLam-oss/obsidian-wechat-converter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/DavidLam-oss/obsidian-wechat-converter/main/.claude/commands/openprd/fleet.mdgit clone --depth 1 https://github.com/DavidLam-oss/obsidian-wechat-converterWrote 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/davidlam-oss/obsidian-wechat-converter/fleet)<a href="https://agentmods.dev/commands/davidlam-oss/obsidian-wechat-converter/fleet"><img src="https://agentmods.dev/badge/commands/davidlam-oss/obsidian-wechat-converter/fleet.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 | $0.00000 | $0.00180 |
| Opus 5 | $0.00000 | $0.00090 |
| Sonnet 5 | $0.00000 | $0.00036 |
| Haiku 4.5 | $0.00000 | $0.00018 |
Grade A, and why
fleet 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 3d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- openprd-fleet — 95% identical, 2 lines differ
What it actually says
OpenPrd Fleet
Audit or update historical projects. Start with openprd fleet <root> --dry-run; use --sync-registry to backfill the global workspace registry, --backfill-work-units for historical PRD identity binding, --update-openprd for projects that already have .openprd/ or legacy root openprd/changes|specs|archive/changes artifacts, and reserve --setup-missing for explicitly selected projects.
For interactive OpenPrd work, rebuild state from .openprd/ before acting. In unattended automation, skip OpenPrd context/gates unless the task explicitly opts into OpenPrd.
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.
- 3d ago First seen · 13 lines · 0 tokens per session scan A 34326cd45d9c
fleet is a command published in the GitHub repository DavidLam-oss/obsidian-wechat-converter (306 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 180 tokens. 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 2026-09-04.
Other commands, from other repositories
template
Manage issue templates for streamlined issue creation.
sync-linear
Sync current work with Linear ticket status.
add-note
Add an internal or external note to a ConnectWise PSA ticket.
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
dispatcher
Pick the next-best repo to work on across the portfolio — rank free repos, recommend one, claim its lease atomically, and route to the entry command.
workpm
A project-management workflow for coordinating multiple AI workers through five stages. It includes task assignment, shared activity logs, worker replacement, and final checks.