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 skills add P47Phoenix/Claude-Plugins --skill evaluativegit clone --depth 1 https://github.com/P47Phoenix/Claude-PluginsWrote 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/skills/p47phoenix/claude-plugins/evaluative)<a href="https://agentmods.dev/skills/p47phoenix/claude-plugins/evaluative"><img src="https://agentmods.dev/badge/skills/p47phoenix/claude-plugins/evaluative/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/skills/p47phoenix/claude-plugins/evaluative"><img src="https://agentmods.dev/badge/skills/p47phoenix/claude-plugins/evaluative.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 | $0.00074 | $0.01292 |
| Opus 5.5 | $0.00030 | $0.00517 |
| Sonnet 5.5 | $0.00015 | $0.00258 |
| Haiku 4.5 | $0.00007 | $0.00129 |
Grade A, and why
research-types-evaluative 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evaluative Research Sub-Skill
Router-dispatched paradigm sub-skill for Evaluative research. Not directly model-invocable; the research-agent parent loads this sub-skill only when Phase 1 detection classifies the question as Evaluative.
When This Sub-Skill Loads
The parent router dispatches here when the input question contains signals like:
- "Did X work" / "Was X effective"
- "What was the impact of X"
- "Is X worth it"
- "Evaluate X" / "Assess X"
- Post-launch retrospectives, ROI assessments, "should we keep using X"
Disambiguation rule (from research-agent/references/research-type-patterns.md):
"What is the current adoption of X" (mapping a fact) → Descriptive. "Was X adoption successful" (judging merit) → Evaluative.
Framework Selection
| Framework | Use When |
|---|---|
| PICO | Default for Evaluative — intervention X is being judged against a comparison C on outcome O |
| PECO | Population was exposed to X (not actively choosing); evaluating the resulting effect |
| None | Single-option pre-post evaluation with no comparison group available |
PICO is the canonical Evaluative framework. SPICE applies only when the evaluation is qualitative/experiential rather than outcome-based.
Output Pattern: Impact Assessment
Use this pattern verbatim for the Findings section (parent skill's Phase 6 Synthesis output):
## Research Type: Evaluative
## Framework: PICO
P: [Population/context]
I: [Intervention/subject being evaluated]
C: [Comparison baseline]
O: [Outcomes measured]
## Inclusion/Exclusion Criteria
Include: [...]
Exclude: [...]
Date range: [from] to [to]
## Evidence Summary Table
| ID | Source | Design | Scope | Outcome Direction | GRADE |
|----|--------|--------|-------|-------------------|-------|
| S1 | ... | ... | ... | + / - / neutral | ⊕⊕⊕◯ |
## Outcome Synthesis
- Positive outcomes: [count / proportion of sources]
- Negative / neutral outcomes: [count / proportion]
- Heterogeneity: [Are results consistent or conflicting? Why?]
## Risk of Bias Summary
| Source | Selection | Performance | Detection | Attrition |
|--------|-----------|-------------|-----------|-----------|
| S1 | Low | ... | ... | ... |
## Verdict
[Conclusion with overall GRADE level and caveats]
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 · 113 lines · 74 tokens per session scan A 6905efd98c08
research-types-evaluative is a skill published in the GitHub repository P47Phoenix/Claude-Plugins (2 stars, last pushed 2d ago), licensed MIT. It adds 74 tokens to every session and 1,292 once invoked, about $0.0003 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 2026-08-31.
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