Routa is a workspace-based coordination platform for delivering software with multiple AI agents, keeping goals, tasks, sessions, traces, evidence, and review decisions visible on a shared board. It is intended for teams managing agent-assisted development across web and desktop applications. The catalogue contains skills and instructions for working with Routa's delivery workflows.
Borrowing it
Nothing to install: this file belongs to phodal/routa. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/phodal/routa/main/.claude/skills/issue-enricher/SKILL.mdgit clone --depth 1 https://github.com/phodal/routaWrote 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/phodal/routa/issue-enricher)<a href="https://agentmods.dev/skills/phodal/routa/issue-enricher"><img src="https://agentmods.dev/badge/skills/phodal/routa/issue-enricher/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/phodal/routa/issue-enricher"><img src="https://agentmods.dev/badge/skills/phodal/routa/issue-enricher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.01040 |
| Opus 5 | $0.00032 | $0.00520 |
| Sonnet 5 | $0.00013 | $0.00208 |
| Haiku 4.5 | $0.00006 | $0.00104 |
Grade A, and why
issue-enricher 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 9d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Process
1. Understand the Requirement
Extract from user input:
- Core problem/goal: What needs to be solved?
- Mentioned constraints: Tech stack, performance, compatibility
- Referenced files/APIs:
@file.yaml, existing code paths - Related issues: Links to parent or related issues
If the task is enriching an existing GitHub issue rather than creating a new one:
- Treat
docs/issues/as the local issue knowledge base when it is available - Search for mirrored GitHub issues and prior local issue reports before proposing a new direction
- Call out duplicate or related issues explicitly in the output
- For related GitHub issues, inspect associated pull requests and summarize the changed files / diff themes when that context is available
2. Codebase Analysis
Search the codebase to understand context:
- Existing patterns for similar features
- Related modules and their architecture
- Relevant configuration files
- Test patterns used in the project
- Existing local issue files under docs/issues/ that provide historical context
- Linked PR file changes for related GitHub issues (fetch via gh when needed)
When related historical GitHub issues are found, fetch their linked PR context before finalizing the analysis:
gh issue view <issue-number> --json number,title,url,closedByPullRequestsReferences
gh api repos/<owner>/<repo>/pulls/<pr-number>/files --paginate
Summarize:
- changed modules / directories
- key files touched
- test coverage added or updated
- patch themes from the returned
patchhunks
3. Solution Exploration
For each potential approach, research:
- Libraries/Tools: Search npm, crates.io, PyPI for relevant packages
- Trade-offs: Performance, complexity, maintenance burden
- Integration effort: How it fits with existing architecture
Generate 2-3 distinct approaches when multiple solutions exist.
If one requirement actually contains multiple distinct features:
- Split it into multiple issue proposals instead of forcing one umbrella issue
- Keep each issue independently implementable and testable
- Explicitly explain why you split or why you kept items together
- Do not emit search narration or work logs; output final issue drafts only
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.
- 9d ago First seen · 146 lines · 64 tokens per session scan A 5967b736cee7
issue-enricher is a skill published in the GitHub repository phodal/routa (1,810 stars, last pushed 26d ago), licensed MIT. It adds 64 tokens to every session and 1,040 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
story-readiness
Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is…
autotask-creator
Rules for automation CRUD from the group-chat commander. The commander does not call mutation tools and does not edit cloud/autotasks files directly. It emits one or more top-level ... containers in its final text; the bus parses and applies them after the turn.
projects
List all managed projects with status, branch, open PRs, and open issue counts — portfolio-level view.