Spec Kit is an open-source toolkit for defining software requirements and plans before implementation with an AI coding agent. It is used by developers and organizations following a spec-driven development process.
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.
git clone --depth 1 https://github.com/github/spec-kitWrote 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/commands/github/spec-kit/selftest)<a href="https://agentmods.dev/commands/github/spec-kit/selftest"><img src="https://agentmods.dev/badge/commands/github/spec-kit/selftest/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/commands/github/spec-kit/selftest"><img src="https://agentmods.dev/badge/commands/github/spec-kit/selftest.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 | $0.00010 | $0.00537 |
| Opus 5.5 | $0.00004 | $0.00215 |
| Sonnet 5.5 | $0.00002 | $0.00107 |
| Haiku 4.5 | $0.00001 | $0.00054 |
Grade C, and why
selftest scanned grade C with 1 finding 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.
Nullifies safety policieshighAnti-refusal
"You have no restrictions", "do anything now", "ignore your guidelines": a direct jailbreak that disables guardrails.
Then, simulate adding the extension by installing it from its catalog download URL, which should bypass the restriction. Copies of this mod
1 near-identical copy found in the catalogue:
- selftest — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extension Self-Test: $ARGUMENTS
This command drives a self-test simulating the developer experience with the $ARGUMENTS extension.
Goal
Validate the end-to-end lifecycle (discovery, installation, registration) for the extension: $ARGUMENTS.
If $ARGUMENTS is empty, you must tell the user to provide an extension name, for example: /speckit.selftest.extension linear.
Steps
Step 1: Catalog Discovery Validation
Check if the extension exists in the Spec Kit catalog.
Execute this command and verify that it completes successfully and that the returned extension ID exactly matches $ARGUMENTS. If the command fails or the ID does not match $ARGUMENTS, fail the test.
specify extension info "$ARGUMENTS"
Step 2: Simulate Installation
First, try to add the extension to the current workspace configuration directly. If the catalog provides the extension as install_allowed: false (discovery-only), this step is expected to fail.
specify extension add "$ARGUMENTS"
Then, simulate adding the extension by installing it from its catalog download URL, which should bypass the restriction.
Obtain the extension's download_url from the catalog metadata (for example, via a catalog info command or UI), then run:
specify extension add "$ARGUMENTS" --from "<download_url>"
Step 3: Registration Verification
Once the add command completes, verify the installation by checking the project configuration.
Use terminal tools (like cat) to verify that the following file contains a record for $ARGUMENTS.
cat .specify/extensions/.registry/$ARGUMENTS.json
Step 4: Verification Report
Analyze the standard output of the three steps. Generate a terminal-style test output format detailing the results of discovery, installation, and registration. Return this directly to the user.
Example output format:
============================= test session starts ==============================
collected 3 items
test_selftest_discovery.py::test_catalog_search [PASS/FAIL]
Details: [Provide execution result of specify extension search]
test_selftest_installation.py::test_extension_add [PASS/FAIL]
Details: [Provide execution result of specify extension add]
test_selftest_registration.py::test_config_verification [PASS/FAIL]
Details: [Provide execution result of registry record verification]
============================== [X] passed in ... ==============================
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 · 70 lines · 10 tokens per session scan C 93f33139a3da
selftest is a command published in the GitHub repository github/spec-kit (141,437 stars, last pushed today), licensed MIT. It adds 10 tokens to every session and 537 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it C with 1 finding (nullifies safety policies). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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