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/microsoft/eval-guide/eval-suite-plannernpx skills add microsoft/eval-guide --skill eval-suite-plannergit clone --depth 1 https://github.com/microsoft/eval-guideWhat 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 | $0.00122 | $0.02076 |
| Opus 5 | $0.00061 | $0.01038 |
| Sonnet 5 | $0.00024 | $0.00415 |
| Haiku 4.5 | $0.00012 | $0.00208 |
Grade A, and why
eval-suite-planner 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
This skill produces the Plan artifact of the /eval-guide lifecycle: a populated copy of the customer's Eval Suite Planning & Logging Template plus an interactive HTML review page. The workbook is the source-of-truth artifact; do not replace it with a scenario table, quality-signal table, generic spreadsheet, default .docx report, or HTML-only plan.
The skill aligns to skills/eval-guide/playbook.md and skills/eval-guide/eval-suite-template.md. Use the 10-step playbook as the methodology spine and the XLSX template as the output shape.
Core rule
Copy the blank XLSX template and populate existing cells/rows only. Do not modify the template.
Do not rename sheets, add sheets, delete sheets, add columns, change headers, rewrite README text, edit Dropdown Lists, change styles, change data validation, or convert the template into a different spreadsheet.
If a blank template workbook is available in the session, use it. If not, ask the user to provide the template; do not silently invent a new workbook.
Question policy
Ask targeted questions only when a workbook field materially affects the plan and cannot be inferred safely:
- Eval owner / named approver.
- Lifecycle stage and target deployment decision.
- Whether the agent is prompt-only, RAG/knowledge-grounded, or agentic with tools/connectors.
- Regulated/compliance obligations.
- Authoritative sources and source owners.
If the user wants speed or cannot answer, populate TBD - confirm before baseline.
Planning method
When invoked as /eval-suite-planner <agent description>:
- Extract or infer the agent's purpose, users, knowledge sources, capabilities, boundaries, architecture, lifecycle stage, and known risks.
- Populate Step 1 — Plan the Eval Effort:
- one-sentence eval objective;
- five-factor risk tier: reach, criticality of error, autonomy/blast radius, regulatory/compliance exposure, data sensitivity;
- one accountable owner.
- Define eval sets, not scenarios:
- Capability eval sets: one row per capability dimension that must be diagnostic, e.g. accuracy/correctness, faithfulness/groundedness, relevancy, style/tone, reasoning/tool use.
- Trust & Safety eval sets: one row per refusal, boundary, or safety category, e.g. guardrails, out-of-scope handling, sensitive-data handling, prompt injection/jailbreak, compliance-specific behavior.
- Apply Step 4 v5 gates/improvement-target logic:
- T&S sets use absolute pass-rate hard gates, usually near 100%.
- Capability sets usually use a launch floor for first deployment plus regression/direction after baseline, not a standing absolute pass-rate target.
- High-risk capabilities that function like guardrails keep explicit hard floors.
- Use the template's existing
Target pass rate,Target rationale,Gate type,Intended use,Run cadence, andNotescolumns to express this; do not add a new column.
- Specify Step 5 human inputs:
- grading rubric, ground truth, golden answer, or rubric + ground truth;
- author/owner;
- grounding source dependency;
- whether source changes require review.
- Plan Step 6 grader validation without changing the template:
- record grader type and validation expectation in the registry row's
Notes; - for LLM-as-judge / Custom rubrics, note that human-labeled hard and borderline cases must validate the judge before baseline scores are trusted;
- for programmatic checks, note the deterministic check to confirm;
- for human grading, note reviewer agreement expectations where relevant.
- record grader type and validation expectation in the registry row's
- Seed Step 7 baseline placeholders in
3 . Run Logonly when useful:- one placeholder row per eval set;
Run type = Baseline;- result fields blank;
Actionable next step = Validate grader, then run baseline;Status = Open.
- Apply Step 8 regression partitioning in existing registry fields:
- capability sets usually
Intended use = BothorRegression; - most T&S sets are
Gate; the slim subset likely affected by model/tool/policy changes can beBothorRegression; - set
Run cadenceusing existing dropdown values such asPer-change,Nightly,Weekly, orMilestone-only.
- capability sets usually
- Flag Step 10 reusable assets in
4 . Reusable Library:- reusable T&S sets;
- grading rubrics;
- failure-pattern templates;
- production-derived edge-case categories when applicable.
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 · 162 lines · 0 tokens per session scan A 205e6d8352f1
eval-suite-planner is a skill published in the GitHub repository microsoft/eval-guide (127 stars, last pushed 2mo ago), licensed MIT. It adds 122 tokens to every session and 2,076 once invoked, about $0.0006 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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