Borrowing it
Nothing to install: this file belongs to alecs5am/ralphy. 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/alecs5am/ralphy/main/.agents/skills/dev-issues/SKILL.mdgit clone --depth 1 https://github.com/alecs5am/ralphyWrote 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/alecs5am/ralphy/dev-issues)<a href="https://agentmods.dev/skills/alecs5am/ralphy/dev-issues"><img src="https://agentmods.dev/badge/skills/alecs5am/ralphy/dev-issues/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/alecs5am/ralphy/dev-issues"><img src="https://agentmods.dev/badge/skills/alecs5am/ralphy/dev-issues.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 | $0.00269 | $0.01545 |
| Opus 5.5 | $0.00108 | $0.00618 |
| Sonnet 5.5 | $0.00054 | $0.00309 |
| Haiku 4.5 | $0.00027 | $0.00154 |
Grade A, and why
dev-issues 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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dev-issues — brain-dump → distributed issues
A maintainer skill. It does not touch .ralphy/workspaces/<ws>/projects/ or call media models. It converts an unstructured stream of thoughts into a set of correctly-shaped notes/issues/*.md work items. Pairs with /dev-loop, which executes the issues this skill files.
When it fires
- The user tags
/dev-issuesand then writes a lot — a wall of ideas, gripes, product direction, "and also we should…". The longer and less structured the input, the more this skill earns its keep. - ALSO FIRE when a normal dev conversation produces ≥3 distinct actionable threads the user wants preserved before they evaporate.
- DO NOT FIRE for one scoped task (do it, or file a single note via
dev-tasks), for content production, or for one-off idea/decision capture into thenotes/inbox (dev-tasks).
Workflow
-
Read the inputs first. Read
notes/README.md(the note shape + the Issues folder layout),docs/developing-ralphy.md(English-only rule, the lint suite), and skim the active backlog (the flat top level ofnotes/issues/) plusnotes/ideas/so you know what already exists.notes/issues/done/andnotes/issues/deprecated/are the closed archive — skim them only during collision-check (step 3).dev-tasksis the sibling skill fornotes/inbox capture (ideas / decisions).Status-by-folder.
notes/issues/is split into the flat top level (the live backlog),done/(resolved / promoted-and-landed), anddeprecated/(superseded / won't-do). New issues are always filed at the flat top level. Each issue keeps its> **Status:**line in sync with its folder. -
Decompose the brain-dump into discrete items. One issue = one coherent unit of work (one verb / file / feature / refactor / bug). Split compound thoughts; merge near-duplicates. Aim for issues a single sub-agent could execute end-to-end.
-
Collision-check before filing each. Search all of
notes/issues/(active top level +done/+deprecated/) andnotes/ideas/for an existing entity that already covers the thought. If one exists, update it (or note the overlap) rather than spawning a duplicate. If the match lives indone/, the thought is likely a regression or follow-up —git mvit back to the active top level and reset its> **Status:**line, or file a fresh issue that cross-links it. Never let the same thing live in two places.
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 · 49 lines · 269 tokens per session scan A 9a8c53d15c3d
dev-issues is a skill published in the GitHub repository alecs5am/ralphy (140 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 269 tokens to every session and 1,545 once invoked, about $0.0011 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 skills, from other repositories
video-gen
Use when generate videos with AI models — Runway, Kling, Sora, Pika, Seedance 2.0, Grok Imagine, Veo. Text-to-video, image-to-video, video extension, multi-modal references. Use when generating video from text prompts, animating images, or creating AI video content.
clinical-reports
Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation…
imaging-data-commons
Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.
clinical-decision-support
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading…
molecular-cloning
Molecular cloning simulation and design. PCR amplicon prediction, restriction enzyme digestion, Golden Gate and Gibson assembly simulation, primer design, CRISPR sgRNA design, and plasmid annotation. For protein-level sequence analysis use biopython or esm; for database lookups use gene-database or ensembl-database.
geo-database
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.