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/echoingvesper/mcp-task-orchestrator/commands-guidegit clone --depth 1 https://github.com/EchoingVesper/mcp-task-orchestratorWrote 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/echoingvesper/mcp-task-orchestrator/commands-guide)<a href="https://agentmods.dev/commands/echoingvesper/mcp-task-orchestrator/commands-guide"><img src="https://agentmods.dev/badge/commands/echoingvesper/mcp-task-orchestrator/commands-guide.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 | $0.00000 | $0.01965 |
| Opus 5 | $0.00000 | $0.00983 |
| Sonnet 5 | $0.00000 | $0.00393 |
| Haiku 4.5 | $0.00000 | $0.00197 |
Grade A, and why
commands-guide 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 4d 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 — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Task Orchestrator Commands Guide
Quick reference for all available commands in this project.
PRP (Project Requirement Planning) Commands
/PRPs:prp-base-create [feature description]
Purpose: Create comprehensive feature implementation PRPs with context engineering
When to use: Starting new feature development with full planning
Example: /PRPs:prp-base-create user authentication system with OAuth2
/PRPs:prp-base-execute @PRP-file.md
Purpose: Execute a PRP with enhanced validation and orchestrator integration
When to use: Implementing features from completed PRPs
Example: /PRPs:prp-base-execute @PRPs/user-auth-implementation.md
/PRPs:prp-planning-create [rough idea]
Purpose: Transform rough ideas into comprehensive PRDs with visual documentation
When to use: Early ideation phase, need market research and user story development
Example: /PRPs:prp-planning-create real-time collaboration features
/PRPs:prp-spec-create [transformation goal]
Purpose: Create specification-driven PRPs for refactoring/transformation projects
When to use: Modernizing existing code, architectural changes, migration projects
Example: /PRPs:prp-spec-create migrate database layer to async SQLAlchemy
/PRPs:prp-spec-execute @SPEC-file.md
Purpose: Execute specification-driven transformations with security validation
When to use: Implementing architecture changes, refactoring projects
Example: /PRPs:prp-spec-execute @PRPs/async-db-migration-spec.md
/PRPs:prp-task-create [specific task]
Purpose: Create focused task PRPs for smaller implementations
When to use: Bug fixes, small features, specific technical tasks
Example: /PRPs:prp-task-create add rate limiting to API endpoints
/PRPs:prp-task-execute @task-file.md
Purpose: Execute focused task implementations
When to use: Implementing specific technical tasks or bug fixes
Example: /PRPs:prp-task-execute @PRPs/add-rate-limiting-task.md
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.
- 4d ago First seen · 198 lines · 0 tokens per session scan A ec927c321981
commands-guide is a command published in the GitHub repository EchoingVesper/mcp-task-orchestrator (28 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,965 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 2026-08-30.
Other commands, from other repositories
proyecto
Declara el proyecto activo (scope global) para atribucion de coste/horas en agentactions. Sin argumento, muestra el proyecto actual.
svsi-review
/svsi-review {slug} # modo interactivo en sesión Claude Code /svsi-review --batch {file} # delega a predrivereview.py (tmux, no en sesión) /svsi-review --stats # métricas acumuladas desde SQLite.
instinct-status
Shows learned instincts from dqiii8.db, grouped by project and confidence. Internal diagnostic tool — not for user invocation.
checkpoint
Works for you. Go outside and live. — AI orchestrator that auto-routes tasks to the cheapest model that solves them. 70% run free on local models. Self-auditing, self-improving, zero prompting skill needed. Built with vibe coding by a finance student. Your models, your data.
weekly-review
Works for you. Go outside and live. — AI orchestrator that auto-routes tasks to the cheapest model that solves them. 70% run free on local models. Self-auditing, self-improving, zero prompting skill needed. Built with vibe coding by a finance student. Your models, your data.
mobilize
Works for you. Go outside and live. — AI orchestrator that auto-routes tasks to the cheapest model that solves them. 70% run free on local models. Self-auditing, self-improving, zero prompting skill needed. Built with vibe coding by a finance student. Your models, your data.