Borrowing it
Nothing to install: this file belongs to weselow/Yandex-webmaster-mcp-server. 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/weselow/Yandex-webmaster-mcp-server/master/.claude/skills/subagents-discipline/SKILL.mdgit clone --depth 1 https://github.com/weselow/Yandex-webmaster-mcp-serverWrote 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/weselow/yandex-webmaster-mcp-server/subagents-discipline)<a href="https://agentmods.dev/skills/weselow/yandex-webmaster-mcp-server/subagents-discipline"><img src="https://agentmods.dev/badge/skills/weselow/yandex-webmaster-mcp-server/subagents-discipline/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/weselow/yandex-webmaster-mcp-server/subagents-discipline"><img src="https://agentmods.dev/badge/skills/weselow/yandex-webmaster-mcp-server/subagents-discipline.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 | $0.00011 | $0.00997 |
| Opus 5 | $0.00005 | $0.00498 |
| Sonnet 5 | $0.00002 | $0.00199 |
| Haiku 4.5 | $0.00001 | $0.00100 |
Grade B, and why
subagents-discipline scanned grade B with 2 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 12d 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
curl -X POST localhost:3000/api/users -d '{"name":"test"}' -H "Content-Type: application/json" Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| API endpoint | `curl` the endpoint, check response | Write integration test | How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Principles
Rule 0: Read the Bead First
Before implementing anything, read the bead comments for context:
bd show {BEAD_ID}
bd comments {BEAD_ID}
The orchestrator's dispatch prompt is automatically logged as a DISPATCH comment on the bead. This contains:
- The investigation findings
- Root cause analysis (file, function, line)
- Related files that may need changes
- Gotchas and edge cases
Use this context. Don't re-investigate. The comments contain everything you need to implement confidently.
If no dispatch or context comments exist, ask the orchestrator to provide context before proceeding.
Rule 1: Look Before You Code
Before writing code that touches external data (API, database, file, config):
- Fetch/read the ACTUAL data - run the command, see the output
- Note exact field names, types, formats - not what docs say, what you SEE
- Code against what you observed - not what you assumed
WITHOUT looking first:
Assumed: column is "reference_images"
Reality: column is "reference_image_url"
Result: Query fails
WITH looking first:
Ran: SELECT column_name FROM information_schema.columns WHERE table_name = 'assets';
Saw: reference_image_url
Coded against: reference_image_url
Result: Works
Rule 2: Test Functionally (Close the Loop)
Principle: Optimize for the fastest way to verify your work actually works.
| You built | Fast verification | Slower alternative |
|---|---|---|
| API endpoint | curl the endpoint, check response |
Write integration test |
| Database change | Run migration, query the result | Write migration test |
| Frontend component | Load in browser, interact with it | Write component test |
| CLI tool | Run the command, check output | Write unit test |
| Config change | Restart service, verify behavior | N/A — just verify |
Two strategies:
- User Journey Tests — Test actual behavior as a user experiences it:
# API: curl with real data curl -X POST localhost:3000/api/users -d '{"name":"test"}' -H "Content-Type: application/json" # CLI: run the command bd create "Test" -d "Testing" && bd list # Error case: curl with invalid auth curl -X POST localhost:3000/api/users -H "Authorization: Bearer invalid"
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.
- 12d ago First seen · 128 lines · 11 tokens per session scan B facb3eb5c28c
subagents-discipline is a skill published in the GitHub repository weselow/Yandex-webmaster-mcp-server (5 stars, last pushed 1mo ago), licensed MIT. It adds 11 tokens to every session and 997 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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