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 cboone/agent-harness-plugins --skill plant-defectsgit clone --depth 1 https://github.com/cboone/agent-harness-pluginsWrote 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/cboone/agent-harness-plugins/plant-defects)<a href="https://agentmods.dev/skills/cboone/agent-harness-plugins/plant-defects"><img src="https://agentmods.dev/badge/skills/cboone/agent-harness-plugins/plant-defects/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/cboone/agent-harness-plugins/plant-defects"><img src="https://agentmods.dev/badge/skills/cboone/agent-harness-plugins/plant-defects.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 | $0.00058 | $0.02210 |
| Opus 5.5 | $0.00023 | $0.00884 |
| Sonnet 5.5 | $0.00012 | $0.00442 |
| Haiku 4.5 | $0.00006 | $0.00221 |
Grade A, and why
plant-defects 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 3d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plant Defects
The discipline of deliberately breaking code to prove a test can see it.
A test asserts a property of the code. Planting a defect asserts a property of the test, and the second does not follow from the first. Where a check is an external instrument, or where its claim is an absence, the second property has a bad default answer and reading the source cannot improve it.
When to Use
Use this when a check's own correctness is in question rather than the code's. The three signals, in descending order of urgency:
- The claim is an absence. No leak, no race, no unused import, no warning, nothing left behind. A search for absence succeeds for the wrong reason when the instrument was never running.
- The check is an external instrument. A sanitizer, a linter, a formatter, a leak checker, a conformance validator. Its exit code answers a question you did not ask, and its silence has two readings.
- The failure mode is a weakening rather than a break. A release store simplified to relaxed, a tolerance widened, two correct lines put in the wrong order. Each compiles and each passes, which is what separates this from a defect the compiler already refuses.
Do not use this to re-derive coverage for ordinary code whose failure is a legible compile error or an obviously failing test. The compiler is already telling you.
Core Principles
- The second property has a bad default answer. "This test would catch that" is a claim about the test. Until it has been run against the defect it names, it is a prediction.
- Order the assertions. Establish that the instrument was running, then that the subject ran and its output parses, and only then read the absence. What is invariant is that no absence is believed before the first two; which of them comes first depends on the instrument, and the strong form of the first (an arm built to fail) is not always available.
- Record what happened, not what was expected. A result column filled in from the issue that filed the work is not a measurement. Several of the findings behind this skill are cases where the two differed.
- Encoding a plant is not the same as covering it. A plant far enough outside a bound is caught by a sibling check, so the arm that names it is asserting only that the error had a detectable sign. Weaken each assertion in turn and confirm something still fails.
- A plant that does not compile is not a passing plant. Judge on the build's exit code, not the shape of its output, or a grep for failures reads a compile error as a pass.
- Instruments do not compose by assumption. Tabulate defect against instrument and mark what each one cannot see. Where a row turns out to be covered by nothing, say so deliberately rather than leaving it implicit. A matrix that covers every row is a fine outcome; the point is to measure the cells, not to manufacture a gap.
What ships with it
6 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.
- 3d ago Changed 420c6643b256
- 8d ago Changed · +2 lines · +20 tokens per session 3224ae226efa
- 26d ago Changed · -11 lines · -169 tokens per session c44f3975f90a
- 1mo ago First seen · 112 lines · 207 tokens per session scan A a703531d420d
plant-defects is a skill published in the GitHub repository cboone/agent-harness-plugins (2 stars, last pushed yesterday), licensed MIT. It adds 58 tokens to every session and 2,210 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-13.
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