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 skills add LLM-Coding/Semantic-Anchors --skill socratic-code-theory-recoverygit clone --depth 1 https://github.com/LLM-Coding/Semantic-AnchorsWrote 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/llm-coding/semantic-anchors/socratic-code-theory-recovery)<a href="https://agentmods.dev/skills/llm-coding/semantic-anchors/socratic-code-theory-recovery"><img src="https://agentmods.dev/badge/skills/llm-coding/semantic-anchors/socratic-code-theory-recovery.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00115 | $0.02598 |
| Opus 5 | $0.00057 | $0.01299 |
| Sonnet 5 | $0.00023 | $0.00520 |
| Haiku 4.5 | $0.00012 | $0.00260 |
Grade A, and why
socratic-code-theory-recovery 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 9d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Socratic Code-Theory Recovery
Reverse-engineer a bounded context into documentation without hallucinating the parts the code cannot tell you.
On invocation
When this skill is invoked:
-
Check whether the user named a bounded context. Look at the same message that invoked the skill and at the immediately preceding messages. A valid bounded-context pointer is a path (relative or absolute) to a directory, plus a short human-readable name for what the context is (e.g.
src/auth, "Authentication"). If both are present, proceed to Phase 1. -
If no bounded context is named, ask for it before doing anything else. Do not start Phase 1 against the current working directory by default — Phase 1 produces files (
QUESTION_TREE-<context-name>.adoc,OPEN_QUESTIONS-<context-name>.adoc) and running it on the wrong directory wastes work. Ask exactly:Which bounded context should I apply Socratic Code-Theory Recovery to? Give me a directory path (the bounded context's code root) and a short human-readable name. If you want the whole current repo treated as one bounded context, say so explicitly.
-
Once you have the pointer, run Phase 1. Use prompts/phase-1-question-tree.md — substitute
[bounded context path]with the user's path and[context-name]with the kebab-cased human-readable name. Do not change the leaf classification, Q-ID scheme, or the output-file naming scheme. -
Stop after Phase 1. Tell the user that Phase 1 is complete, where the two output files are, and that the next step is routing
OPEN_QUESTIONS-<context-name>.adocto the team. Phase 2 is gated on the file, not on being asked: before starting Phase 2 — even when the user explicitly requests it — check that every[OPEN]leaf inOPEN_QUESTIONS-<context-name>.adochas either a team answer or an explicit(deferred)marker. If any leaf has neither, do not run Phase 2; list the unanswered leaves instead.
When to use this skill
Use this skill on a brownfield codebase when:
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 134 lines · 115 tokens per session scan A 049ed1bedd29
socratic-code-theory-recovery is a skill published in the GitHub repository LLM-Coding/Semantic-Anchors (467 stars, last pushed 7d ago), licensed Apache-2.0. It adds 115 tokens to every session and 2,598 once invoked, about $0.0006 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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