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/datit309/supergraph/plannpx skills add datit309/supergraph --skill plangit clone --depth 1 https://github.com/datit309/supergraphWhat 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 | $0.00037 | $0.01239 |
| Opus 5 | $0.00018 | $0.00620 |
| Sonnet 5 | $0.00007 | $0.00248 |
| Haiku 4.5 | $0.00004 | $0.00124 |
Grade A, and why
plan 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 yesterday.
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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/supergraph:plan
Scan codebase, map blast radius, create machine-readable plan.
Announce: "📐 /supergraph:plan — scanning codebase, creating plan..."
Quick Gate
< 20 lines, ≤2 files, no hub/bridge, complexity <10 → skip to /supergraph:tdd.
Steps
0. Read CONTEXT.md (if exists):
cat CONTEXT.md 2>/dev/null | head -60
Use domain vocabulary from CONTEXT.md in all plan task descriptions — never use raw file/class names where a domain term exists.
1. Read the codebase (MANDATORY before planning):
- Read config file → language, framework, versions
- Read 2-3 source files near target area → naming, imports, error handling
- Read 1-2 test files → test structure, assertion style
2. Ensure graph: Reuse /supergraph:scan context. If not done → run scan first. Requires CBM_PROJECT + healthy index_status; if stale/degraded → index_repository (absolute path).
3. Graph analysis (parallel where independent): See references/codebase-memory-contract.md#Lifecycle. Run detect_changes, search_graph, trace_path (inbound/outbound/data-flow), and get_architecture (overview/clusters/boundaries/hotspots) in parallel (no dependencies). After get_graph_schema, run recipes hubs, bridges, test-gaps, cross-boundary (requires schema). Derive risk from evidence; preserve escalation: >20 files STOP, hub/bridge needs approval. Respect scan: TTL — skip index_repository if fresh per scan logic.
3b. Serena (optional): See serena/SKILL.md:Setup. If scan not run, call initial_instructions first, then find_referencing_symbols/find_implementations for key symbols. Cross-check with graph blast radius; persist callers via write_memory only if >10 files or hub/bridge. Skip if Serena unavailable.
4. Discuss approach (MANDATORY, user's language): Present findings 1-3 (naming/patterns, graph risk, task summaries). Get approval before step 5; revise if needed.
5. Create plan tasks — each task 2-5 min. Use exact machine-readable format:
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.
- yesterday First seen · 105 lines · 37 tokens per session scan A ffa9209ff3ca
plan is a skill published in the GitHub repository datit309/supergraph (21 stars, last pushed 4d ago), licensed MIT. It adds 37 tokens to every session and 1,239 once invoked, about $0.0002 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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