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/chris-dare-dev/agent-kitWrote 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/chris-dare-dev/agent-kit/roadmap)<a href="https://agentmods.dev/commands/chris-dare-dev/agent-kit/roadmap"><img src="https://agentmods.dev/badge/commands/chris-dare-dev/agent-kit/roadmap/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/commands/chris-dare-dev/agent-kit/roadmap"><img src="https://agentmods.dev/badge/commands/chris-dare-dev/agent-kit/roadmap.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 | $0.00124 | $0.05252 |
| Opus 5.5 | $0.00050 | $0.02101 |
| Sonnet 5.5 | $0.00025 | $0.01050 |
| Haiku 4.5 | $0.00012 | $0.00525 |
Grade A, and why
roadmap 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 1mo 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 — 381 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Roadmap Orchestrator
You are the orchestrator. The main session IS the pipeline. Subagents cannot spawn subagents — every dispatch comes from here.
A four-phase gated roadmap builder. Auto-advances within a phase; gates between phases ONLY when there is an architecturally divergent fork the user must resolve. Always gates on external writes per workspace CLAUDE.md.
Phase 1 REFINE → roadmap-refiner → ## Goal section in plans/<slug>-roadmap.md
Phase 2 DECOMPOSE → roadmap-decomposer → ## Epics section
Phase 3 SEQUENCE → roadmap-sequencer → ## Roadmap — Now / Next / Later section
Phase 4 MATERIALIZE → roadmap-materializer → ## Cross-references + optional GitLab drafts
Parsing $ARGUMENTS
<slug-or-topic>— everything before the first--. Used verbatim as the brief if short and specific (≤40 chars, kebab-case → slug). If longer prose, treat as the brief and derive the slug from it (kebab-case, ≤40 chars).--gitlab— Phase 4 materializer drafts GitLab issue bodies. The orchestrator presents the drafts and waits for explicit user authorization before calling/issue-create.--iteration <id>— if--gitlaband issues are created, assign them to this iteration id.--resume— skip the init check; read the existing roadmap doc and jump to the first unpopulated section.
If $ARGUMENTS is empty, check whether the current conversation contains a problem being discussed. If yes, derive the brief from the conversation (see Step 0). If no problem context exists, STOP and ask: "What would you like to roadmap?"
When to invoke / When NOT to invoke
Invoke for:
- Multi-epic plans (≥ 2 epics spanning ≥ 2 weeks of work)
- When the user says "plan this project", "build a roadmap for X", "decompose this into milestones", "what's the path to ship Y", "help me sequence this work"
- Mid-conversation: the user has been discussing a problem and now wants a structured plan
Do NOT invoke for:
- Single milestone known and well-scoped → go straight to
/milestone-pipeline <id> - Single-issue ticket creation → use
/issue-create - Status or promotion check → use
/env-promotion-diff,/argocd-status - Re-plan of an already-shipped milestone → write
plans/<slug>-retrospective.mddirectly;/roadmapis forward-looking - No problem statement at all → STOP and ask what the user wants to roadmap
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.
- 1mo ago First seen · 381 lines · 124 tokens per session scan A f3274f304d5b
roadmap is a command published in the GitHub repository chris-dare-dev/agent-kit (0 stars, last pushed 2mo ago), licensed MIT. It adds 124 tokens to every session and 5,252 once invoked, about $0.0005 per session on Opus 5.5. 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 commands, from other repositories
template
Manage issue templates for streamlined issue creation.
fest-show
Show festival progression (in-progress tasks, roadmap, and dependency view).
add-note
Add an internal or external note to a ConnectWise PSA ticket.
sync-linear
Sync current work with Linear ticket status.
dispatcher
Use when you want the orchestrator to pick the next repo to work on across your whole portfolio — it enumerates candidate repos below the confinement root, resolves free/busy from each repo's session.lock lease, ranks the FREE ones by backlog priority × staleness × readiness, recommends the single most worthwhile one…
workpm
A project-management workflow for coordinating multiple AI workers through five stages. It includes task assignment, shared activity logs, worker replacement, and final checks.