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 The-AI-Directory-Company/agents-and-skills --skill ticket-writinggit clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-skillsWrote 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/the-ai-directory-company/agents-and-skills/ticket-writing)<a href="https://agentmods.dev/skills/the-ai-directory-company/agents-and-skills/ticket-writing"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/ticket-writing/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/the-ai-directory-company/agents-and-skills/ticket-writing"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/ticket-writing.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 | $0.00025 | $0.01443 |
| Opus 5 | $0.00013 | $0.00722 |
| Sonnet 5 | $0.00005 | $0.00289 |
| Haiku 4.5 | $0.00003 | $0.00144 |
Grade A, and why
ticket-writing 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ticket Writing
Before you start
Gather the following from the user:
- What needs to be built/changed? (Feature, fix, refactor, or chore)
- Why? (Link to PRD, user report, incident, or business goal)
- What's the tech stack? (Languages, frameworks, database, hosting)
- What's the team context? (How familiar is the team with this area of the codebase?)
If the user gives you a vague request ("write tickets for search"), push back: "What specific behavior should search have? What does the user see today vs. what should they see?"
Ticket template
Use the following template for every ticket:
Title
Use the format: [Action verb] [specific thing] [context]
Good: "Add rate limiting to /api/search endpoint (10 req/s per user)" Bad: "Fix search" or "Search improvements" or "Rate limiting"
Context
2-3 sentences explaining WHY this work matters. Link to the parent epic, PRD, or incident. The engineer should understand the business motivation without reading another document.
The /api/search endpoint currently has no rate limiting, which allowed a single
user to generate 50k requests in an hour last Tuesday (INC-234), degrading
search performance for all users. This ticket adds per-user rate limiting to
prevent abuse while maintaining normal usage patterns.
Acceptance Criteria
Write specific, testable conditions. Use the format:
- [ ] Given [precondition], when [action], then [expected result]
- [ ] Given a user has made 10 requests in the last second,
when they make an 11th request,
then they receive a 429 response with a Retry-After header
- [ ] Given a user has been rate-limited,
when the rate limit window expires,
then their next request succeeds normally
- [ ] Rate limit configuration (requests per second, window size)
is stored in environment variables, not hardcoded
Rules for acceptance criteria:
- Every criterion must be independently verifiable
- Include both the happy path AND edge cases
- Include error/failure states explicitly
- If there are performance requirements, state them with numbers
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.
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 · 155 lines · 25 tokens per session scan A 586f8e9f2e22
ticket-writing is a skill published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 25 tokens to every session and 1,443 once invoked, about $0.0001 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
starting-a-new-project
Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.
customer-success
Support workflows, ticketing systems (Zendesk, Intercom), knowledge base design, chatbot design, and metrics (CSAT, NPS). Use when building support infrastructure, designing help centers, or optimizing customer experience.
event-planner
Event planning with timelines, budgets, vendor coordination, logistics checklists, and post-event evaluation. Use when organizing conferences, workshops, galas, or corporate events.
hr-talent
HR and talent management expertise for talent acquisition, performance management, compensation strategy, organizational design, culture building, succession planning, and D&I programs. Use when hiring, managing performance, designing organizations, or building culture.
innovation
Innovation management expertise for innovation frameworks (Design Thinking, Stage-Gate), ideation processes, innovation portfolio management, venture capital, open innovation, and IP strategy. Use when driving innovation, managing R&D portfolios, or building innovation programs.
leadership
Executive leadership expertise for decision-making, change management, crisis management, stakeholder management, team building, and organizational leadership. Use when leading teams, managing change, navigating crises, or developing leadership skills.