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.
npx skills add LerianStudio/ring --skill planning-small-featuresgit clone --depth 1 https://github.com/LerianStudio/ringWrote 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/lerianstudio/ring/planning-small-features)<a href="https://agentmods.dev/skills/lerianstudio/ring/planning-small-features"><img src="https://agentmods.dev/badge/skills/lerianstudio/ring/planning-small-features.svg" alt="Measured on agentmods" 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 | $0.00085 | $0.01174 |
| Opus 5 | $0.00043 | $0.00587 |
| Sonnet 5 | $0.00017 | $0.00235 |
| Haiku 4.5 | $0.00009 | $0.00117 |
Grade A, and why
ring:planning-small-features 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 5d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Small Track Pre-Dev Workflow (4 Gates)
When to use
- Feature takes <2 days to implement
- Uses existing architecture patterns
- Doesn't add new external dependencies
- Doesn't create new data models/entities
- Doesn't require multi-service integration
- Can be completed by a single developer
Skip when
- Feature is complex (>=2 days) - use ring:planning-large-features instead
- Adds new dependencies, data models, or architecture patterns
Sequence
Runs before: ring:running-dev-cycle, ring:executing-plans
Related
Complementary: ring:planning-large-features, ring:creating-worktrees, ring:product-designer + ring:validating-ux-completeness (standalone UX step, recommended when feature has UI) Skills orchestrated:
- ring:researching-features
- ring:writing-prds
- ring:writing-trds
- ring:writing-plans
Running the Small Track pre-development workflow for features that take <2 days, use existing patterns, add no new external dependencies, create no new data models, require no multi-service integration, and can be completed by a single developer.
For complex features (any of the above false), use ring:planning-large-features instead.
Gate Map
| Gate | Skill | Output |
|---|---|---|
| 0 | ring:researching-features | research.md |
| 1 | ring:writing-prds | prd.md |
| 2 | ring:writing-trds | trd.md |
| 3 | ring:writing-plans | plan.md |
All artifacts saved to: docs/pre-dev/<feature-name>/
Step 1: Gather Feature Name
AskUserQuestion: "What is the name of your feature?" (kebab-case, e.g., "user-logout", "email-validation")
Step 2: Topology Discovery (MANDATORY)
Execute topology discovery per shared-patterns/topology-discovery.md. Store as TopologyConfig for all subsequent gates.
Step 3: Gather Feature-Specific Inputs
Q2 (CONDITIONAL): Auth requirements — auto-detect from go.mod (lib-auth present → skip). Options: None, User only, User + permissions, Service-to-service, Full.
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.
- 5d ago First seen · 100 lines · 85 tokens per session scan A ba777aeeb38f
ring:planning-small-features is a skill published in the GitHub repository LerianStudio/ring (211 stars, last pushed 19d ago), licensed Apache-2.0. It adds 85 tokens to every session and 1,174 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
ds-ship
Ship orchestrator — classify the project, pick a mode (improve/release/launch/maintain), delegate only the skills the project's signals justify, consolidate findings, produce an audit report. Use for an end-to-end audit or ship pipeline across multiple skills.
trajectory
Internal dynos-work skill. Sequence memory manager. Stores compact task traces and retrieves similar prior tasks to inform discovery and design review. Runs only when the user explicitly types /dynos-work:trajectory; never auto-triggered from conversation.
repair
Internal dynos-work skill. Manually repair one specific finding without running the full audit loop (/dynos-work:audit handles repair automatically). Runs only when the user explicitly types /dynos-work:repair; never auto-triggered from conversation.
ds-build
Plan executor — take an issue, a specs/{feature}/tasks.md, or a plain request and implement it unit by unit with a verify signal per unit, red-proven tests, budgeted backtracking, and a code-proven close. Use when the plan exists and the work is to be done, not planned.
list
Internal dynos-work skill. List all registered dynos-work projects. Runs only when the user explicitly types /dynos-work:list; never auto-triggered from conversation.
ds-issue
GitHub-Issues lifecycle in one skill — file a verified deduped issue, sweep the set for duplicates, audit done-ness from code, and execute an issue end-to-end (re-verify → impact map → implement → code-proven close). Use to open, refine, sweep, status-check, or do an issue.