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/ulises-jeremias/agentic-workstationWrote 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/agents/ulises-jeremias/agentic-workstation/dots-workstation-lead)<a href="https://agentmods.dev/agents/ulises-jeremias/agentic-workstation/dots-workstation-lead"><img src="https://agentmods.dev/badge/agents/ulises-jeremias/agentic-workstation/dots-workstation-lead/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/agents/ulises-jeremias/agentic-workstation/dots-workstation-lead"><img src="https://agentmods.dev/badge/agents/ulises-jeremias/agentic-workstation/dots-workstation-lead.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 | $0.00028 | $0.00214 |
| Opus 5 | $0.00014 | $0.00107 |
| Sonnet 5 | $0.00006 | $0.00043 |
| Haiku 4.5 | $0.00003 | $0.00021 |
Grade A, and why
dots-workstation-lead 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 10d 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
You are the agentic-workstation Dev Companion team lead.
Follow dots-workstation-assistant routing and skill-catalog.yaml. Select the right companion layer:
- Generic:
dots-workstation-dev-companion+dots-workstation-workflow-generic-project - Client/account overlay: load the matching workspace pack, then use
dots-workstation-dev-companion+dots-workstation-workflow-generic-project
Before making changes:
- Read
AGENTS.mdand repo docs. - Load account/team pack if present under
~/.local/share/agentic-workstation/dev-companion/packs/. - Enforce boundaries: do not operate outside allowed paths.
If the task is large, delegate to specialized subagents (reviewer, data-validator, forge-pr).
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.
- 10d ago First seen · 19 lines · 28 tokens per session scan A 73e152bf1b35
dots-workstation-lead is an agent published in the GitHub repository ulises-jeremias/agentic-workstation (2 stars, last pushed 7d ago), licensed MIT. It adds 28 tokens to every session and 214 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 2026-08-31.
Other agents, from other repositories
debugger
Debugging specialist for errors and test failures. Use when encountering build errors, runtime exceptions, test failures, or unexpected behavior. Invoke with /debugger to investigate issues.
verifier
Validates completed work. Use after tasks are marked done to confirm implementations are functional. Invoke with /verifier when you need to verify code actually works.
learnship-executor
Executes a single learnship PLAN.md atomically — one task at a time with per-task commits, deviation handling, and SUMMARY.md creation. Spawned by execute-phase on platforms with subagent support.
learnship-planner
Creates executable PLAN.md files for a phase — decomposes goals into vertical slice (tracer bullet) tasks with wave-ordered dependency analysis. Each plan delivers one demoable user-facing behavior end-to-end. Spawned by plan-phase on platforms with subagent support.
learnship-solution-writer
Analyzes a recently solved problem and produces a structured solution document for .planning/solutions/ with YAML frontmatter. Spawned by compound workflow on platforms with subagent support.
learnship-code-reviewer
Reviews code changes through a specific persona lens (correctness, testing, security, performance, maintainability, adversarial) and returns structured findings with severity and confidence. Spawned by the review workflow on platforms with subagent support.