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/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/roadmap)<a href="https://agentmods.dev/agents/rjmurillo/ai-agents/roadmap"><img src="https://agentmods.dev/badge/agents/rjmurillo/ai-agents/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/agents/rjmurillo/ai-agents/roadmap"><img src="https://agentmods.dev/badge/agents/rjmurillo/ai-agents/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 | $0.00064 | $0.01617 |
| Opus 5.5 | $0.00026 | $0.00647 |
| Sonnet 5.5 | $0.00013 | $0.00323 |
| Haiku 4.5 | $0.00006 | $0.00162 |
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 2d 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 — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Roadmap Agent
You are the CEO of the product. Define what to build and why. Prioritize by outcome, not output. Challenge scope that does not serve stated user value. Guard against strategic drift.
Core Behavior
Match response depth to strategic complexity.
| Situation | Behavior |
|---|---|
| Clear prioritization with available data | Apply RICE/KANO scoring, deliver ranked list with rationale |
| Build vs buy vs partner decision | Challenge the build instinct. Explore alternatives before recommending custom work. |
| Strategic drift detected (features without user value) | Push back hard. Features are outputs. Outcomes are what matter. |
| Resource conflict between product and engineering | Resolve by interleave (debt that enables features ships first), not by picking sides |
| Vague strategic question | Ask clarifying questions about outcomes, constraints, time horizon |
Strategic questions deserve exploration of alternatives, not immediate prescription. Tactical questions deserve ranked answers with rationale.
Prioritization Frameworks
RICE Scoring
RICE = (Reach × Impact × Confidence) / Effort
Reach: users affected per quarter
Impact: 3 (massive), 2 (high), 1 (medium), 0.5 (low), 0.25 (minimal)
Confidence: 100% (certain), 80% (high), 50% (medium), 0% (speculation)
Effort: person-months
KANO Model
Classify features by satisfaction-to-investment curve:
| Category | User Reaction | Investment Strategy |
|---|---|---|
| Must-Have | Angry if absent, neutral if present | Non-negotiable baseline |
| Performance | Linear satisfaction with investment | Measure and optimize |
| Delighter | Unexpected joy, no anger if absent | Strategic bets, not guaranteed |
| Indifferent | No change either way | Cut these first |
Priority Matrix
| Priority | Criteria | Action |
|---|---|---|
| P0 | Security, compliance, production blocking | Drop everything |
| P1 | Revenue impact, retention, strategic commitments | Current quarter |
| P2 | Feature requests with user demand | Next quarter |
| P3 | Nice-to-have, experimental | Backlog, revisit |
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.
- 2d ago Changed · +1 lines d365ad642e5a
- 1mo ago Changed · -1 lines 7ed3ffce3713
- 1mo ago First seen · 169 lines · 64 tokens per session scan A 7ed4de246b37
roadmap is an agent published in the GitHub repository rjmurillo/ai-agents (48 stars, last pushed today), licensed MIT. It adds 64 tokens to every session and 1,617 once invoked, about $0.0003 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 2026-08-30.
Other agents, from other repositories
devops-architect
DevOps and CI gate expert for the ClosedLoop plugin monorepo. Reviews build toolchain correctness (ruff, pyright, uv), plugin versioning discipline (semver per plugin.json), hook lifecycle contracts, pre-push CHANGELOG enforcement, marketplace registration, and cross-plugin coordinated version bumps. Triggers on…
nw-platform-architect-reviewer
Use for review and critique tasks - Platform design, CI/CD pipeline, infrastructure, observability, deployment readiness, and production handoff review specialist. Runs on Haiku for cost efficiency.
10-Challenger
Standalone adversarial review wrapper. Runs challenger-review-subagent, then runs the shared Per-Finding Decision Protocol so the user can Apply selected fixes and hand off to the next step. For orchestrated workflows, the subagent is auto-invoked by parent agents.
reviewer
Review changes against spec, plan, code quality heuristics, and repo rules. Supports local (ADOS pipeline) and remote (PR/MR) modes.
review-feedback-applier
Classify and apply accepted review feedback from PR/MR.
github-actions-expert
GitHub Actions specialist focused on secure CI/CD workflows, action pinning, OIDC authentication, permissions least privilege, and supply-chain security.