Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/agentic-community/mcp-gateway-registrynpx agentmods add skills/agentic-community/mcp-gateway-registry/writingWrote 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/agentic-community/mcp-gateway-registry/writing)<a href="https://agentmods.dev/skills/agentic-community/mcp-gateway-registry/writing"><img src="https://agentmods.dev/badge/skills/agentic-community/mcp-gateway-registry/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/agentic-community/mcp-gateway-registry/writing"><img src="https://agentmods.dev/badge/skills/agentic-community/mcp-gateway-registry/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 | $0.00069 | $0.03265 |
| Opus 5.5 | $0.00028 | $0.01306 |
| Sonnet 5.5 | $0.00014 | $0.00653 |
| Haiku 4.5 | $0.00007 | $0.00327 |
Grade A, and why
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 13d 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Writing Skill
If you want people to read your stuff, follow Orwell's rules.
LLMs are not your friends. They write in passive voice, mix figures of speech that do not fit together, and pad every sentence with -ly words. Cut all of it.
Orwell's rules
- Never use a metaphor, simile, or other figure of speech which you are used to seeing in print.
- Never use a long word where a short one will do.
- If it is possible to cut a word out, always cut it out.
- Never use the passive where you can use the active.
- Never use a foreign phrase, a scientific word, or a jargon word if you can think of an everyday English equivalent.
- Break any of these rules sooner than say anything outright barbarous.
Rule 6 outranks the other five. A stiff sentence that obeys rules 1-5 is worse than a plain one that breaks one of them.
How to apply each rule
1. No stock figures of speech
Kill any phrase you have read a hundred times. If two images sit in one sentence, they will clash and the reader sees nothing.
Ban list, not exhaustive: game changer, at the end of the day, low-hanging fruit, moving the needle, paradigm shift, deep dive, unlock value, seamless, robust, journey, landscape, ecosystem (unless you mean living things), leverage as a verb, delve, tapestry, testament to, navigate the complexities.
Use a plain statement, or invent an image that fits the thing you are describing.
- Bad: This release is a game changer that unlocks seamless value across the ecosystem.
- Good: This release cuts registry startup from 40 seconds to 3.
2. Short words
Prefer the short word every time: use not utilize, help not facilitate, start not commence, about not approximately, use not leverage, get not obtain, show not demonstrate, need not necessitate, before not prior to, after not subsequent to, so not accordingly, most not the majority of, can not possesses the capability to.
3. Cut words
Delete every word that carries no weight. Common padding: in order to, the fact that, it should be noted that, it is important to note, as previously mentioned, in terms of, with respect to, a number of, at this point in time, basically, essentially, actually, really, very, quite, simply, just.
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.
- 13d ago First seen · 199 lines · 69 tokens per session scan A 1f3fa2d507a5
writing is a skill published in the GitHub repository agentic-community/mcp-gateway-registry (984 stars, last pushed today), licensed Apache-2.0. It adds 69 tokens to every session and 3,265 once invoked, about $0.0003 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 2026-10-03.
Other skills, from other repositories
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
python-feature-lifecycle
Guidance for package and feature lifecycle in the Agent Framework Python codebase, including stage meanings, feature-stage decorators, feature enums, and how to move APIs from one stage to the next.
python-development
Coding standards, conventions, and patterns for developing Python code in the Agent Framework repository. Use this when writing or modifying Python source files in the python/ directory.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
memory-retain
Save what was learned to Hindsight long-term memory. Use when a task finishes, when the user states a fact, decision or preference, and when you discover something a later run or another Bot would need.
security-conductor
Operating procedure for the kirocrew-security-conductor agent. Use when a security conductor session is seeded, inspected or debugged. Run vulnerability discovery on one target as a supervised fleet — one auditor per attack surface, an independent verifier per finding, two human gates.