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 leifericf/agentic-sdk --skill extend-conformance-corpusgit clone --depth 1 https://github.com/leifericf/agentic-sdkWrote 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/leifericf/agentic-sdk/extend-conformance-corpus)<a href="https://agentmods.dev/skills/leifericf/agentic-sdk/extend-conformance-corpus"><img src="https://agentmods.dev/badge/skills/leifericf/agentic-sdk/extend-conformance-corpus.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.00972 |
| Opus 5 | $0.00023 | $0.00486 |
| Sonnet 5 | $0.00009 | $0.00194 |
| Haiku 4.5 | $0.00005 | $0.00097 |
Grade A, and why
extend-conformance-corpus 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 4d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
extend-conformance-corpus
Grow the corpus a differential probe runs against a reference implementation. This is a write-tests specialization: every tuple is a test whose expected output is captured from the reference, never hand-written, so every assertion can fail and none can lie. The probe, fixtures, and capture tooling already exist; this recipe only decides what new forms enter the corpus. It never edits the probe.
Pick targets first
Rank untargeted surface, not favorites:
- Public vars the project implements that have zero corpus tuples (diff the census or surface inventory against the corpus's var set).
- Vars implicated by open bug reports or recent divergence fixes.
- Hot vars whose misbehavior a user meets on day one.
A generation unit takes a small batch (five to ten vars), not the whole backlog: ground truth capture and triage stay reviewable per batch.
Two tiers, cheap one first
- Palette tier (free). Mechanical application of the var across the fixed edge-value palette the capture tool defines (empty collections, nil, zero and negative, extreme integers, exact and inexact numbers, chars, symbols, infinite sequences). Declare it; the tool expands it. Combinations that throw in the reference are recorded as non-ok ground truth and filtered, so a throwing cell costs nothing but a corpus entry. Spend no judgment here.
- Judgment tier. Hand-reasoned forms for what the palette cannot reach: laziness and chunk-realization observability (count the calls with a side-effect probe), numeric-tower promotion chains, tie-breaking and stability, init-element semantics on empty input, early-termination protocols, pad and step extremes, grammar corners of string formatters, interactions between two vars. Reason about the var's contract and write the forms that would expose a wrong implementation strategy, not merely a wrong answer.
What never enters the corpus
- Nondeterminism. No randomness, wall clocks, object identity hashes, iteration order beyond what the reference guarantees.
- Ambient effects. No filesystem, network, environment reads; a side-effect probe is fine only when self-contained (a local atom).
- Forms that throw in the reference. The pipeline diffs printed values; a reference throw is filtered, so an error-shape probe here is a wasted entry. Error conformance is its own probe family.
- Host-type name probes. Where the project's type names are a
designed divergence or a frozen compat surface,
(class x)-style probes only generate noise; probe observable behavior instead. - Unbounded output. Wrap infinite structures in a bounded take; respect the print bounds the harness binds.
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.
- 4d ago First seen · 92 lines · 46 tokens per session scan A 3d597c6a1672
extend-conformance-corpus is a skill published in the GitHub repository leifericf/agentic-sdk (5 stars, last pushed 6d ago), licensed MIT. It adds 46 tokens to every session and 972 once invoked, about $0.0002 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 2026-09-03.
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