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/dr-code/tessera/plan-reviewnpx skills add dr-code/tessera --skill plan-reviewgit clone --depth 1 https://github.com/dr-code/tesseraWhat 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 | $0.00030 | $0.00680 |
| Opus 5 | $0.00015 | $0.00340 |
| Sonnet 5 | $0.00006 | $0.00136 |
| Haiku 4.5 | $0.00003 | $0.00068 |
Grade A, and why
plan-review 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/plan-review — Independent Plan Review via Codex
Usage
/plan-review path/to/plan.md
/plan-review — reads plan from current conversation context or asks user to provide it
Description
Send an implementation plan to GPT via Codex CLI for structured review before implementation begins. Claude synthesizes GPT's feedback, agrees or disagrees with each point, and issues a go/no-go verdict.
Instructions
Phase 0: Load Plan + Tessera Context
If tessera MCP is configured in this session:
1. graph_continue (mandatory first call)
2. graph_action_summary — surface locked decisions that may constrain the plan
3. graph_retrieve with the plan's key feature terms — find relevant existing code
- If a file path was provided: read the plan file
- If no path: ask the user to paste the plan or specify where it is
- Include the retrieved context and any locked decisions in the GPT review prompt so it can flag contradictions with existing patterns
Phase 1: Send to GPT
Construct the review prompt with the full plan text and any codebase context:
codex exec "You are reviewing an implementation plan before execution begins. Plan: <PLAN_TEXT>. Codebase context: <CONTEXT>. Review for: (1) architecture violations or inconsistency with existing patterns, (2) missing edge cases or error handling, (3) wrong ordering of steps or missing dependencies between steps, (4) security concerns, (5) over-engineering or unnecessary complexity. For each issue: ISSUE: <description> | SUGGEST: <specific fix> | SEVERITY: HIGH/MED/LOW. End with VERDICT: approved OR needs_revision"
Phase 2: Claude Synthesizes
For each GPT issue, Claude responds:
- AGREE — the plan needs to change here; note what revision is required
- DISAGREE — explain why the plan already handles it or why GPT's concern is inapplicable
- PARTIAL — the concern is valid but the suggested fix is wrong; propose a better fix
Phase 3: Output
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 · 64 lines · 30 tokens per session scan A ea3df69358cf
plan-review is a skill published in the GitHub repository dr-code/tessera (1 stars, last pushed 21d ago), licensed MIT. It adds 30 tokens to every session and 680 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 2026-08-31.
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