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 commands/ddunnock/claude-plugins/concept.documentgit clone --depth 1 https://github.com/ddunnock/claude-pluginsWhat 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 | $0.00023 | $0.01625 |
| Opus 5 | $0.00012 | $0.00813 |
| Sonnet 5 | $0.00005 | $0.00325 |
| Haiku 4.5 | $0.00002 | $0.00162 |
Grade A, and why
concept:document 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 2d 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 — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/concept:document
Phase 5 of concept development: document generation.
Prerequisites
Run the prerequisite gate check:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/update_state.py --state .concept-dev/state.json check-gate document
If this exits non-zero, stop and tell the user to complete the previous phase first.
Then load context:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/update_state.py --state .concept-dev/state.json show- Read all artifacts:
.concept-dev/IDEAS.md.concept-dev/PROBLEM-STATEMENT.md.concept-dev/BLACKBOX.md.concept-dev/DRILLDOWN.md
Procedure
Step 1: Set Phase
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/update_state.py --state .concept-dev/state.json set-phase document
Step 2: Pre-Generation Review
Present a summary of all inputs:
===================================================================
DOCUMENT GENERATION
===================================================================
Inputs:
IDEAS.md — [N] themes, [N] ideas
PROBLEM-STATEMENT — [1-sentence summary]
BLACKBOX.md — [N] functional blocks, [Approach name]
DRILLDOWN.md — [N] sub-functions, [N] sources, [N] gaps
I will generate two documents:
1. CONCEPT DOCUMENT
Modeled on engineering concept papers:
Exec Summary → Problem → Concept → Capabilities →
ConOps → Maturation Path → Glossary
2. SOLUTION LANDSCAPE
Per-domain approaches with pros/cons, citations,
confidence ratings, and unresolved gaps
Each section will be presented for your approval before
being included in the final document.
Ready to begin?
===================================================================
Step 3: Mandatory Assumption Review
Before generating any document content, run the assumption review gate:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/assumption_tracker.py --registry .concept-dev/assumption_registry.json review
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.
- 2d ago First seen · 265 lines · 23 tokens per session scan A 1f34dcebc58d
concept:document is a command published in the GitHub repository ddunnock/claude-plugins (12 stars, last pushed 5mo ago), licensed MIT. It adds 23 tokens to every session and 1,625 once invoked, about $0.0001 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.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.