debug-specs

A debugging process for Plain applications that traces a reported problem from generated code back to the original .plain specification files. Generated files are evidence only; fixes are made in the specifications.

In plain words
What is it for?
Investigating unexpected application behavior, reading generated code to find the cause, diagnosing failing tests, and correcting only the relevant .plain files.
Why use it?
It keeps fixes in the source files that control generation, so they are not lost the next time code is generated. It also gives a structured way to investigate crashes, visual issues, and failing tests.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/plainlang/plain-forge/debug-specs
Any agent
npx skills add plainlang/plain-forge --skill debug-specs
Clone the repo
git clone --depth 1 https://github.com/plainlang/plain-forge

Made for: Claude Code, Codex.

Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,266 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 2d ago against content hash 196f722553e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

forge/skills/debug-specs/SKILL.md · 190 lines

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

  1. The module name — identifies the plain_modules/<module_name>/ directory (code/ and tests/) and the corresponding .plain file(s).
  2. 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."
  3. Optional: a specific functional spec — if the user suspects a particular spec, start there. Otherwise, investigate broadly.

Phase 1 — Understand the Context

  1. Read the .plain file(s) for the module — frontmatter, definitions, implementation reqs, test reqs, and all functional specs. Also read import and requires chains.
  2. 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.

Read the full file on GitHub · 190 lines

Changes

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.

  1. 2d ago First seen · 190 lines · 64 tokens per session scan A 196f722553e7

Subscribe to this mod's changes

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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