Borrowing it
Nothing to install: this file belongs to alexandme/textql-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/alexandme/textql-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/alexandme/textql-mcpWrote 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/instructions/alexandme/textql-mcp/agents-md)<a href="https://agentmods.dev/instructions/alexandme/textql-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/alexandme/textql-mcp/agents-md/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/instructions/alexandme/textql-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/alexandme/textql-mcp/agents-md.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 | $0.02037 | $0.02037 |
| Opus 5.5 | $0.00815 | $0.00815 |
| Sonnet 5.5 | $0.00407 | $0.00407 |
| Haiku 4.5 | $0.00204 | $0.00204 |
Grade A, and why
textql-mcp AGENTS.md 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 2mo 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions for the usage of Backlog.md CLI Tool
1. Source of Truth
- Tasks live under
backlog/tasks/(drafts underbacklog/drafts/). - Every implementation decision starts with reading the corresponding Markdown task file.
- Project documentation is in
backlog/docs/. - Project decisions are in
backlog/decisions/.
2. Defining Tasks
Title
Use a clear brief title that summarizes the task.
Description: (The "why")
Provide a concise summary of the task purpose and its goal. Do not add implementation details here. It should explain the purpose and context of the task. Code snippets should be avoided.
Acceptance Criteria: (The "what")
List specific, measurable outcomes that define what means to reach the goal from the description. Use checkboxes (- [ ]) for tracking.
When defining ## Acceptance Criteria for a task, focus on outcomes, behaviors, and verifiable requirements rather
than step-by-step implementation details.
Acceptance Criteria (AC) define what conditions must be met for the task to be considered complete.
They should be testable and confirm that the core purpose of the task is achieved.
Key Principles for Good ACs:
-
Outcome-Oriented: Focus on the result, not the method.
-
Testable/Verifiable: Each criterion should be something that can be objectively tested or verified.
-
Clear and Concise: Unambiguous language.
-
Complete: Collectively, ACs should cover the scope of the task.
-
User-Focused (where applicable): Frame ACs from the perspective of the end-user or the system's external behavior.
- Good Example: "- [ ] User can successfully log in with valid credentials."
- Good Example: "- [ ] System processes 1000 requests per second without errors."
- Bad Example (Implementation Step): "- [ ] Add a new function
handleLogin()inauth.ts."
Task file
Once a task is created it will be stored in backlog/tasks/ directory as a Markdown file with the format
task-<id> - <title>.md (e.g. task-42 - Add GraphQL resolver.md).
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.
- 2mo ago First seen · 189 lines · 2,037 tokens per session scan A b1a69edaff6a
textql-mcp AGENTS.md is an instructions file published in the GitHub repository alexandme/textql-mcp (1 stars, last pushed 1y ago), licensed Apache-2.0. It adds 2,037 tokens to every session, about $0.0081 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 2026-08-31.
textql-mcp AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| textql-mcp AGENTS.mdalexandme/textql-mcp | Instructions file | 1 | 1y ago | Apache-2.0 | A | 2,037 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |