ss-spec

ss-spec is a skill for Codex from bonnguyenitc/specship. It costs 80 tokens per session (2,795 once invoked), scanned A, original, MIT.

A requirements-reading guide that turns a ticket, product requirements document, or feature request into a precise shared understanding. It records goals, requirements, acceptance checks, edge cases, and open questions.

In plain words
What is it for?
Use it as the first stage of a feature, to analyze a specification, confirm acceptance criteria, identify edge cases, and record blockers.
Why use it?
It reduces implementation mistakes caused by misunderstanding what needs to be built. Clarifying the requirements first gives later planning and coding a reliable basis.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: model in frontmatter; mentions subagents; mentions Claude Code.

Good fit Use it as the first stage of a feature, to analyze a specification, confirm acceptance criteria, identify edge cases, and record blockers.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/bonnguyenitc/specship/ss-spec
Install

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.

Any agent
npx skills add bonnguyenitc/specship --skill ss-spec
Clone the repo
git clone --depth 1 https://github.com/bonnguyenitc/specship

Made for: Codex.

Wrote 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.

agentmods badge for ss-spec

README.md
[![agentmods](https://agentmods.dev/badge/skills/bonnguyenitc/specship/ss-spec/github.svg)](https://agentmods.dev/skills/bonnguyenitc/specship/ss-spec)
Your own site
<a href="https://agentmods.dev/skills/bonnguyenitc/specship/ss-spec"><img src="https://agentmods.dev/badge/skills/bonnguyenitc/specship/ss-spec/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.

agentmods 80×15 button for ss-spec

Your own site · 80×15
<a href="https://agentmods.dev/skills/bonnguyenitc/specship/ss-spec"><img src="https://agentmods.dev/badge/skills/bonnguyenitc/specship/ss-spec.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,795 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00080 $0.02795
Opus 5 $0.00040 $0.01398
Sonnet 5 $0.00016 $0.00559
Haiku 4.5 $0.00008 $0.00280

Measured 9d ago against content hash 63185ddb0b2c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

ss-spec 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.

skills/ss-spec/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Spec

Goal: turn a spec into a precise, shared understanding before designing or coding. Most implementation bugs are misunderstood requirements — catch them here.

When to use

  • You're handed a ticket / PRD / feature request to build.
  • Requirements are ambiguous and you need to pin them down before acting.
  • First stage of the workflow: spec → plan → coding → review (+ debug).

Shared task state

Part of the task pipeline — see ../WORKFLOW.md for the full contract. This skill opens the task.

  • Hydrate: if continuing an existing task, read tasks/TASK-<ID>/task.md + spec.md; otherwise pick a new TASK-<ID> and create the folder. Read docs/onboarding/* if present; if those docs are missing and the codebase is unfamiliar, offer to run ss-explore-source first — its output is the convention reference for every later stage.
  • Checkpoint: create/update task.md (the shared state file) alongside spec.md — set stage: spec, spec artifact status draftconfirmed, bump updated:, append a Pipeline Log line carrying your agent label (format: ../WORKFLOW.md → Agent handoff).
  • Blocked? If the spec can't be confirmed because a blocker Q# is waiting on the user or an external answer, set status: blocked, note it in the Now block's Blocked by: line, and log it; flip back to active once it's answered. blocked is involuntary — to set the task aside by choice, use ss-pause-task. See ../WORKFLOW.md → Status values.
  • Lessons: read tasks/LESSONS.md at hydrate and apply its rules; if you detect a process mistake, fix it and append an L# entry there (see ../WORKFLOW.md → Lessons).

Method

1. Read the source completely

  • Read the full spec/ticket and any linked docs, designs, or related issues.
  • Ground it in the actual code, not memory. If the spec references code areas, open them: verify the named files/functions/flags exist, and record the current behavior vs. desired behavior delta — requirements stated against imagined code are the top source of misunderstood specs. Use the ss-explore-source skill if the project is unfamiliar.
  • Delegate heavy exploration to a subagent. When grounding the spec means sweeping a large or unfamiliar codebase (broad "where is X handled?" questions, many candidate files), spawn the ss-explorer agent if your platform can spawn it (ships with specship for Claude Code), else the built-in Explore agent, with a focused brief and ask for structured conclusions, not file dumps - it keeps this thread's context clean for the spec itself. Verify any path or symbol an agent reports before citing it in spec.md. For a small, known area, just read inline — and if your platform can't spawn subagents at all, do the exploration inline too (../WORKFLOW.md → In-stage subagents: delegation is an optimization, never a precondition).

Read the full file on GitHub · 124 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 9d ago First seen · 124 lines · 80 tokens per session scan A 63185ddb0b2c

Subscribe to this mod's changes

ss-spec is a skill published in the GitHub repository bonnguyenitc/specship (2 stars, last pushed 1mo ago), licensed MIT. It adds 80 tokens to every session and 2,795 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 2026-08-31.

Related

Other skills, from other repositories

design-taste-frontend

Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.

Leonxlnx/taste-skill · 61 tokens

html-artifacts

Author the HTML for a plan artifact, dashboard iframe, or Slack attachment — structure, design plan, available runtime, theming, and craft. Read this before writing HTML for saveplan, outputiframe, or slackattachhtml.

langchain-ai/open-swe · 51 tokens

design-taste-frontend-v1

The original v1 taste-skill, preserved for projects depending on its exact behavior. The current default is design-taste-frontend (v2 experimental), which is a substantial rewrite. Use this v1 install name only if you need exact backward compatibility.

Leonxlnx/taste-skill · 61 tokens

brandkit

Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional…

Leonxlnx/taste-skill · 89 tokens

redesign-existing-projects

Upgrades existing websites and apps to premium quality. Audits current design, identifies generic AI patterns, and applies high-end design standards without breaking functionality. Works with any CSS framework or vanilla CSS.

Leonxlnx/taste-skill · 45 tokens

gpt-taste

Elite UX/UI & Advanced GSAP Motion Engineer. Enforces Python-driven true randomization for layout variance, strict AIDA page structure, wide editorial typography (bans 6-line wraps), gapless bento grids, strict GSAP ScrollTriggers (pinning, stacking, scrubbing), inline micro-images, and massive section spacing.

Leonxlnx/taste-skill · 72 tokens