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 skills add mattmre/EVOKORE-MCP-PUBLIC --skill workflow-rungit clone --depth 1 https://github.com/mattmre/EVOKORE-MCP-PUBLICWrote 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/skills/mattmre/evokore-mcp-public/workflow-run)<a href="https://agentmods.dev/skills/mattmre/evokore-mcp-public/workflow-run"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/workflow-run/github.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/skills/mattmre/evokore-mcp-public/workflow-run"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/workflow-run.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00030 | $0.00397 |
| Opus 5 | $0.00015 | $0.00198 |
| Sonnet 5 | $0.00006 | $0.00079 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
workflow-run 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 7d 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
/workflow-run — Execute Workflow DAG Template
Runs a named workflow template from SKILLS/ORCHESTRATION FRAMEWORK/workflow-templates/, orchestrating steps in dependency order.
Usage
/workflow-run "panel-review-generic"
/workflow-run "reverse-engineering-analysis"
/workflow-run "reverse-engineering-improvement-loop"
Available Workflows
| Name | Description |
|---|---|
| panel-review-generic | Multi-expert panel review with parallel expert agents |
| reverse-engineering-analysis | Full binary analysis + report generation |
| reverse-engineering-improvement-loop | Iterative skill improvement with JUDGE gate |
What it does
- Loads
workflow-templates/{name}.jsonfrom the SKILLS directory - Resolves step dependencies into execution order
- Spawns sub-agents for each step (parallel where dependencies allow)
- Collects outputs and passes them to dependent steps
- Returns a summary of all step outcomes
Step Types
agent: Spawns a sub-agent with the step promptskill: Executes a named SKILL.md filebash: Runs a shell command (requires damage-control approval)human: Pauses for human review (HITL gate)
Integration
- Workflow DAGs are stored as JSON in SKILLS/.../workflow-templates/
- Uses AGT-013 (Loop Operator) for step failure detection
- Step outputs feed into the next step's context
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.
- 7d ago First seen · 51 lines · 30 tokens per session scan A 68f492a91d96
workflow-run is a skill published in the GitHub repository mattmre/EVOKORE-MCP-PUBLIC (3 stars, last pushed 3mo ago), licensed MIT. It adds 30 tokens to every session and 397 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 skills, from other repositories
agent-orchestrator
Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.
new-gh-issue-orchestration
Orchestrates a GitHub-issue-driven delivery workflow from issue intake to PR creation using reviewer-first then worker execution. Invoked when the user provides a GitHub issue link/number and asks to start end-to-end delivery.
collaborating
Hackathon-native multiplayer collaboration mode -- brain-dump together, claim tasks across machines, flag decisions async. Drives the subcommands of /forge:collaborate.
work
Dispatch a tracker ticket into an isolated worktree and drive it autonomously to an open pull request, then stop for review. Pass interactive to brainstorm the ticket with a human before planning it, or a sentence of editorial direction as a rider. Use when asked to work a ticket end-to-end.
batch
Dispatch a night's batch of Todo tickets — one worktree and one pull request each — and leave a morning summary. Run explicitly; never inferred.
prep
Spec a ticket before it is dispatched. Brainstorms it, decides everything it can recommend an answer for, asks a present human about the little that survives, and leaves the spec, the decisions and anything still open as one ticket comment. No worktree, no branch, no pull request, and the ticket stays where it was.