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/afaraha8403/balakit/dissectnpx skills add afaraha8403/balakit --skill dissectgit clone --depth 1 https://github.com/afaraha8403/balakitWrote 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/afaraha8403/balakit/dissect)<a href="https://agentmods.dev/skills/afaraha8403/balakit/dissect"><img src="https://agentmods.dev/badge/skills/afaraha8403/balakit/dissect.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 | $0.00143 | $0.04566 |
| Opus 5 | $0.00072 | $0.02283 |
| Sonnet 5 | $0.00029 | $0.00913 |
| Haiku 4.5 | $0.00014 | $0.00457 |
Grade A, and why
dissect 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 5d 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 — 396 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dissect
Leading words: dissect, ground truth, entity-level, minimal-build, red-team, evidence-backed, stub detection, naming audit, fold test, phase separation, patch in place.
Systematically interrogate and optimize an existing service, written plan, or system. The goal is not to rubber-stamp the current design — it is to arrive at the minimal-build plan that correctly meets the requirements, by challenging every assumption with live evidence and an adversarial review panel.
Trigger: /dissect <target> where <target> is a service name, plan file
path, codebase area, or free-form description. If omitted, ask.
dissect is the backward-looking counterpart to deep-deliberation. They share
DNA — parallel read-only sub-agents, devil's-advocate red-teaming, human
checkpoints, evidence over intent — but point in opposite directions:
deliberation designs what to build; dissect audits what already exists.
User Input
$ARGUMENTS
Core principles (never waive)
- Ground truth beats intent. What the code actually does overrides what the plan says it should do. Always verify live.
- Row counts are a liveness signal only. A 0-row table can be load-bearing; a populated table can be redundant. Never use row count as a keep/drop reason.
- Name what it IS, not what it was named. Entities are frequently misnamed.
Read a few actual records before drawing conclusions. A table called
contact_preferencemight store food allergies and golf equipment. - Own vs read. "Entities this service reads" ≠ "entities this service owns." Reading a table does not mean you should count it in the domain.
- Stubs are not live. A function that
throws new Error('not implemented'), a cron that no-ops, or a consumer that re-queues to the DLQ is not a running feature. Check before counting it as active behavior. - Minimal build. Every proposed change must trace to a requirement. Do not design for hypothetical future use. Three similar things beat a premature abstraction.
- Naming audit is phase zero. Naming confusion causes the most incorrect verdicts. Run it before any verdict.
- Sub-agents return evidence, the orchestrator returns verdicts. A sub-agent that declares "VERDICT: DROP" unprompted is overstepping. Synthesis happens in the main context where all evidence is held together.
- Escalate discrepancies, don't resolve them silently. If code says X and the plan says Y, surface both at the checkpoint and let the human decide.
- Patch in place — never rewrite the live plan. If the session is in Cursor
Plan Mode or Claude Plan Mode, or the target is an existing plan document,
the source plan is the document of record. Dissect it, then surgically
update it (fix, tune, fill gaps). Never full-file
Writeit. Never create a second plan that replaces it. Unaddressed sections stay verbatim. Read references/plan_preservation.md before any write. Override only if the human explicitly asks to rewrite from scratch.
What ships with it
3 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.
- 5d ago First seen · 396 lines · 143 tokens per session scan A 9801ce453871
dissect is a skill published in the GitHub repository afaraha8403/balakit (1 stars, last pushed 8d ago), licensed MIT. It adds 143 tokens to every session and 4,566 once invoked, about $0.0007 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 2026-08-31.
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