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/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/delegate)<a href="https://agentmods.dev/commands/sairam0424/mindforge/delegate"><img src="https://agentmods.dev/badge/commands/sairam0424/mindforge/delegate.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/sairam0424/mindforge/delegate"><img src="https://agentmods.dev/badge/commands/sairam0424/mindforge/delegate.svg?style=web" alt="Reviewed on agentmods" width="80" height="15"></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 | $0.00032 | $0.00601 |
| Opus 5 | $0.00016 | $0.00300 |
| Sonnet 5 | $0.00006 | $0.00120 |
| Haiku 4.5 | $0.00003 | $0.00060 |
Grade A, and why
mindforge:delegate 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.
What it actually says
<execution_context> @.mindforge/skills/delegation-patterns/SKILL.md </execution_context>
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Dependency Mapping: Create DAG of dependencies between work packages. Identify critical path (longest dependency chain). Flag packages with >3 dependencies as integration risk. Prioritize breaking dependency cycles (shared interfaces, feature flags, contract testing).
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Team Capability Matrix: Map team members to (skill, seniority, availability). Senior backend (80h), mid frontend (40h part-time), junior fullstack (80h). Match work packages to capability gaps. Flag packages requiring skills not present in team (consultant needed).
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Parallelization Strategy: Assign independent packages to parallel tracks. Track 1 (auth + API) → Person A. Track 2 (UI + state) → Person B. Track 3 (infra + observability) → Person C. Synchronize at integration milestones (sprint boundaries).
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Handoff Protocol: Define deliverable artifacts per package (code + tests + docs + runbook). Specify acceptance criteria (test coverage ≥80%, latency <200ms, accessibility AA). Set review process (PR template, required reviewers, CI gates). Schedule integration sync (twice per sprint).
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Risk Mitigation: Identify single points of failure (one person knows payments). Cross-train on high-risk packages. Set up knowledge transfer sessions. Document critical paths in runbook. Define escalation paths for blockers (TL → EM → Product).
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Communication Cadence: Daily async standup (written updates in Slack). Twice-weekly sync for blockers (30min). Weekly integration demo (show working feature). End-of-sprint retro (what slowed us down). Use DACI for decisions (Driver, Approver, Contributors, Informed).
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 · 38 lines · 32 tokens per session scan A 6ddf7025e298
mindforge:delegate is a command published in the GitHub repository sairam0424/MindForge (0 stars, last pushed 5d ago), licensed MIT. It adds 32 tokens to every session and 601 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 2026-09-03.
Other commands, from other repositories
factory-triage
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factory-sweep
Find Linear tickets that have gone obsolete (duplicate, already shipped, overtaken by events) and retire them with evidence.
factory-audit
Audit this repo against the project-conventions baseline; file the gaps to Linear.
factory-unblock
Re-examine held (ai:blocked) tickets for new evidence and release the ones that no longer need a human.
loops
Weekly review — surface everything in-flight and force a ship / block / kill decision on each.
p5-polish
Collects small clean-up TODOs accumulated during the sprint (from /p5-review, /p5-acceptance, /p5-bugfix, TODO/FIXME comments) that do not justify a full story but make the next sprint easier. Triages each item into polish-now, backlog, handover, or drop. Optionally executes polish-now items directly (TDD mini-cycle…