Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add bjcoombs/ai-native-toolkit/plugin install ai-native-toolkitWrote 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/bjcoombs/ai-native-toolkit/assess-findings)<a href="https://agentmods.dev/skills/bjcoombs/ai-native-toolkit/assess-findings"><img src="https://agentmods.dev/badge/skills/bjcoombs/ai-native-toolkit/assess-findings/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/bjcoombs/ai-native-toolkit/assess-findings"><img src="https://agentmods.dev/badge/skills/bjcoombs/ai-native-toolkit/assess-findings.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 | $0.00067 | $0.13210 |
| Opus 5 | $0.00034 | $0.06605 |
| Sonnet 5 | $0.00013 | $0.02642 |
| Haiku 4.5 | $0.00007 | $0.01321 |
Grade A, and why
assess-findings 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 — 395 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assess Findings Writer
The report-writing half of /assess. The deterministic core has written .assess/run-context.json (the data bus) and the assess-layer-scorer agent has returned the 0-8 scorecard. Your job is to assemble .assess/assess-report.md: the scorecard, the snapshots, the verbatim cross-layer findings, the lying signals, and the Top 3 Actions.
The deterministic parts are not yours to invent - you paste them. You write the prose around a findings section you cannot omit or reorder. This is the deterministic-core-writes-data / LLM-writes-prose split that makes the report reproducible regardless of which model drives the run.
Inputs
$REPO_ROOT/.assess/run-context.json- the data bus (findings, attention, keyhole summary, prescribed actions, stats, diff).- The scorecard returned by the
assess-layer-scoreragent (the 0-8 score, per-layer verdicts, maturity label).
Read the cross-layer findings first
The layers above each measure one axis. The deterministic core also crosses those axes against each other and emits ten named findings - the "where to look" signals no single layer surfaces. Read them once, after the per-layer scans:
jq '.derived_findings, .attention, .keyhole_summary, .prescribed_actions' "$REPO_ROOT/.assess/run-context.json"
derived_findings is a fixed-order list of ten {name, paths, action} objects - all ten always present, paths may be empty. Omit a finding from the report when its paths is empty. Each pairs an axis-crossing with the action it implies:
hidden_coupling- modular statically but bleeds across boundaries historically (files that keep changing together). The static map says "isolated"; git says "coupled." Action: investigate the seam before trusting the boundary.lying_map- high complexity under a stale doc: the map exists but no longer matches the territory. Staleness is the decaying-map churn ratio for a hand-written doc, but for a generated doc that declares provenance (frontmattersource:or a[[generated]]config mapping) it is measured against the source - the doc is stale only when its source is newer than it, so an accurate generated doc is never flagged. Action: fix or delete the doc - a wrong map is worse than none.unexplained_complexity- high complexity with no doc and no recorded intent. Action: write the missing contract. Do not auto-generate it - a guessed contract is just another lying map.untrusted_hotspot(E1 trust axis) - a complexity hotspot whose tests are hollow: an opt-in mutation pass let a high fraction of mutants survive, so the suite runs the code but doesn't pin it. Silent without mutation data (the default read-only run never fires it). Action: strengthen tests to pin observable behaviour, not internal state.self_referential_tests(E2 trust axis) - the code and its co-located tests were introduced in the same commit, so the suite may verify the author's mental model rather than independently-specified behaviour. Action: request human review - the tests verify internal consistency, not truth.unactioned_intent(write-side tendency) - files carrying stale promissory markers (TODO/FIXME/ "remove after migration") that survived many edits to their own file without being kept: a lying map of intent. Silent when the marker scan is unavailable or the history is too thin to age markers. Action: action the promise - fix it, ticket it, or delete the marker/skip.accretion_ratchet(write-side tendency) - a top-band hotspot whose line count only ever ratcheted upward: monotonic net growth across multiple commits with almost no deletion pressure (deletions below ~15% of total churn). The fingerprint of a file appended to rather than reworked. Only surfaced for files already in the top complexity/size band, so a growing-but-simple file is never flagged. Silent when the scan is unavailable, and disclaimed (not dropped) when the git history is degenerate (shallow clone or squashed import). Action: refactor down - extract, delete dead code, or split the file.orphaned_understanding- high complexity with no human anchor and no intent: nobody owns the knowledge. Action: assign a human anchor before further change.candidate_dead_weight- high complexity with no runtime evidence it is live. The bias is to keep (static reachability can't see external callers - Layer 1's caveat applies). Action: verify liveness, then delete only if confirmed dead.refactor_boundary(positive) - high containment: edits stay local. A safe zone, never an attention row. Action: safe to hand an agent in isolation; cite these paths in Strengths.
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 · 395 lines · 67 tokens per session scan A e2e23b0b2ef3
assess-findings is a skill published in the GitHub repository bjcoombs/ai-native-toolkit (30 stars, last pushed today), licensed Apache-2.0. It adds 67 tokens to every session and 13,210 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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