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 stellarshenson/claude-code-plugins/plugin install document-processingWrote 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/commands/stellarshenson/claude-code-plugins/grounding)<a href="https://agentmods.dev/commands/stellarshenson/claude-code-plugins/grounding"><img src="https://agentmods.dev/badge/commands/stellarshenson/claude-code-plugins/grounding/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/commands/stellarshenson/claude-code-plugins/grounding"><img src="https://agentmods.dev/badge/commands/stellarshenson/claude-code-plugins/grounding.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 | $0.00022 | $0.01212 |
| Opus 5.5 | $0.00009 | $0.00485 |
| Sonnet 5.5 | $0.00004 | $0.00242 |
| Haiku 4.5 | $0.00002 | $0.00121 |
Grade A, and why
grounding 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 21d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grounding
Read this plugin's skill file skills/grounding/SKILL.md and follow it. Pure grounding - no tone/style/format compliance (that = /document-processing:validate). Skill always runs document-processing CLI; generative interpretation only on-top layer for semantic claims.
Three modes (skill picks from argument):
- Single claim -
document-processing ground --claim "..." --source <file> --json - One document — full grounding chain (extract → ground → consistency) -
document-processing extract-claims --document <doc> --output validation/claims.json-> reviewclaims.json->document-processing ground --manifest validation/claims.json --source <src1> --source <src2> --output validation/grounding-report.md->document-processing check-consistency --document <doc> --output validation/consistency-report.md. All three steps run; run produces bothgrounding-report.mdandconsistency-report.md. - Many documents -
source_map.yamldeclaringclients[].sources+document(+ optionalprimary_source) ->document-processing validate --manifest source_map.yaml --output-dir validation/, runs same chain per client, producingvalidation/<client>/{claims.json,grounding-report.md,consistency-report.md}
Default engine
Lexical mode is the default: a frozen-weight logistic over 13-18 signals selected by lexical_effort (low / medium / high, default high). All lexical tiers are CPU-only with no extra install required. Use --effort CLI overlay or set lexical_effort in config to switch tiers.
Optional layers (opt-in)
- semantic -
--semanticadds bge-m3 retrieval + reranker (OpenVINO int8, torch-free) - NLI / entailment - the truth signal: cross-encoder reads
(evidence, claim)-> grounded / unconfirmed / contradicted; multilingual, catches contradictions + cross-lingual matches lexical misses - calibration - tune the verdict to your corpus from labelled evidence:
calibrate --action update --evidence f.jsonthenconfig set-calibrator; learned weights live in config. Public-data check:make grounding-validate ENGINE=nli. Full doc:docs/grounding_calibration.md
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.
- 21d ago Changed 0225b5eb34d4
- 1mo ago First seen · 71 lines · 22 tokens per session scan A bd1a7aa06ba8
grounding is a command published in the GitHub repository stellarshenson/claude-code-plugins (4 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 1,212 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.