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 agentmods add skills/plainlang/plain-forge/debug-specsnpx skills add plainlang/plain-forge --skill debug-specsgit clone --depth 1 https://github.com/plainlang/plain-forgeWhat 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 | $0.00064 | $0.02266 |
| Opus 5 | $0.00032 | $0.01133 |
| Sonnet 5 | $0.00013 | $0.00453 |
| Haiku 4.5 | $0.00006 | $0.00227 |
Grade A, and why
debug-specs 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 2d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug Specs
Always use the skill load-plain-reference to retrieve the ***plain syntax rules — but only if you haven't done so yet.
When to Use
- The user observes a bug in the running application (visual, behavioral, crash, performance).
- A conformance test or unit test is failing.
- The generated code does something unexpected or incorrect.
- The user points to a specific functional spec that seems wrong.
Guiding Principle
Generated code in plain_modules/<module>/code/ and plain_modules/<module>/tests/ is read-only — it exists solely as evidence for diagnosis. All fixes are applied exclusively to the .plain spec files. The workflow is: observe → read generated code → trace to spec → fix the spec.
Input
- The module name — identifies the
plain_modules/<module_name>/directory (code/andtests/) and the corresponding.plainfile(s). - The user's observation — what is wrong? This can be a bug description, a screenshot, a test failure, an error message, or a general "this doesn't work right."
- Optional: a specific functional spec — if the user suspects a particular spec, start there. Otherwise, investigate broadly.
Phase 1 — Understand the Context
- Read the
.plainfile(s) for the module — frontmatter, definitions, implementation reqs, test reqs, and all functional specs. Also readimportandrequireschains. - Read the user's observation carefully. Rephrase it back to confirm understanding. Identify:
- What is the expected behavior?
- What is the actual behavior?
- Is this a visual issue, a logic issue, a crash, or a data issue?
Phase 2 — Investigate the Generated Code
Read files in plain_modules/<module_name>/code/ to understand what the renderer produced. Do not modify any generated files.
2a. Narrow the search
If the user pointed to a specific spec or area:
- Identify which generated files implement that spec's behavior.
- Read those files to understand the current implementation.
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.
- 2d ago First seen · 190 lines · 64 tokens per session scan A 196f722553e7
debug-specs is a skill published in the GitHub repository plainlang/plain-forge (55 stars, last pushed 4d ago), licensed MIT. It adds 64 tokens to every session and 2,266 once invoked, about $0.0003 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 2026-08-30.
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