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 commands/sairam0424/mindforge/complete-milestonegit clone --depth 1 https://github.com/sairam0424/MindForgeWrote 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/sairam0424/mindforge/complete-milestone)<a href="https://agentmods.dev/commands/sairam0424/mindforge/complete-milestone"><img src="https://agentmods.dev/badge/commands/sairam0424/mindforge/complete-milestone.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 | $0.00014 | $0.00182 |
| Opus 5 | $0.00007 | $0.00091 |
| Sonnet 5 | $0.00003 | $0.00036 |
| Haiku 4.5 | $0.00001 | $0.00018 |
Grade A, and why
complete-milestone 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 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.
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.
What it actually says
Archive a completed milestone, generate a release report, and prepare the next
milestone. Usage: /mindforge:complete-milestone <name> <version>
Step 1 — Validate milestone completion
Ensure every included phase is verified and has no pending blocking approvals.
Step 2 — Generate milestone report
Summarise shipped phases, notable changes, risks, approvals, and unresolved follow-ups.
Step 3 — Archive milestone artifacts
Archive only the phases included in the milestone, not the entire
.planning/phases/ directory. Preserve history in the archive while keeping
active planning files available in place.
Step 4 — Release metadata
Create the release tag, update STATE.md with milestone summary, and mark the
project ready for the next version.
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 · 23 lines · 14 tokens per session scan A 4abd2a6179af
complete-milestone is a command published in the GitHub repository sairam0424/MindForge (0 stars, last pushed 2d ago), licensed MIT. It adds 14 tokens to every session and 182 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 2026-09-03.
Other commands, from other repositories
factory-ship
Release — open a develop → master PR, wait for CI, merge, verify the deploy.
factory-report
Linear status report across configured repos — queue depth, triage backlog, ready-to-dispatch, blocked/held.
factory-capture
File a Linear issue from this conversation, per the ai:agent-ready protocol — capture only, never implement.
release
Bump version and cut a release.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.