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 bdfinst/agentic-dev-team/plugin install dev-teamWrote 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/agents/bdfinst/agentic-dev-team/token-efficiency-review)<a href="https://agentmods.dev/agents/bdfinst/agentic-dev-team/token-efficiency-review"><img src="https://agentmods.dev/badge/agents/bdfinst/agentic-dev-team/token-efficiency-review/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/agents/bdfinst/agentic-dev-team/token-efficiency-review"><img src="https://agentmods.dev/badge/agents/bdfinst/agentic-dev-team/token-efficiency-review.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 | $0.00023 | $0.01188 |
| Opus 5.5 | $0.00009 | $0.00475 |
| Sonnet 5.5 | $0.00005 | $0.00238 |
| Haiku 4.5 | $0.00002 | $0.00119 |
Grade A, and why
token-efficiency-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 1mo 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implemented by: ${CLAUDE_PLUGIN_ROOT}/scripts/token_efficiency_review.py
Token Efficiency Review
Scope: on-demand Cites: [adversarial-review-protocol] Enforcement: script
Dispatched by the whole-tree /repo-review command, never by
/code-review's per-diff panel (#1733). Its findings (file length, CLAUDE.md
size, LLM anti-patterns) are properties of absolute size and accumulated
drift, not of any single diff's delta — a diff-scoped review of a 20-line PR
can't even see a file that crept past a size threshold over 10 separate small
PRs. select_lenses.py's resolver reads this Scope: on-demand declaration
directly and never selects it for the per-diff roster — the agent body is
the single source of truth for this exclusion, same as any other Scope:
kind.
Output JSON: per ${CLAUDE_PLUGIN_ROOT}/knowledge/review-agent-output-contract.md (Whole-file load: short, canonical schema).
Status: pass=efficient, warn=optimization opportunities, fail=major waste Severity: error=critical waste, warning=significant, suggestion=minor Confidence: high=mechanical (trim verbose rule, extract procedure to skill); medium=verbosity identified, rewrite depends on intent; none=requires human judgment (what detail level is appropriate)
Context needs: full-file
Skip
Return {"status": "skip", "issues": [], "summary": "No Claude Code config or source files in target"} when:
- Target has no CLAUDE.md, rules, skills, or source code files
- Target contains only binary or generated files
Thresholds
| Target | Limit |
|---|---|
| CLAUDE.md | <5000 chars |
| Code examples in CLAUDE.md | ≤10 |
| Rules | ≤200 chars each |
| Skill definitions | ≤2000 chars |
| File length | ≤500 lines |
| Function length | ≤50 lines |
| Nesting depth | ≤5 levels |
| JSDoc comments | ≤15 lines |
| Commented-out code | ≤5 lines total |
Findings
Metric thresholds are enforced by ${CLAUDE_PLUGIN_ROOT}/scripts/token_efficiency_review.py (exit 1 for errors, exit 2 for warnings). This agent provides qualitative analysis for issues the script cannot detect mechanically.
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.
- 1mo ago First seen · 140 lines · 23 tokens per session scan A 8729c925c195
token-efficiency-review is an agent published in the GitHub repository bdfinst/agentic-dev-team (295 stars, last pushed 4d ago), licensed MIT. It adds 23 tokens to every session and 1,188 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 2026-08-30.
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