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 hoanghaoha/survy-agent-skills --skill survey-analysisgit clone --depth 1 https://github.com/hoanghaoha/survy-agent-skillsWrote 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/hoanghaoha/survy-agent-skills/survey-analysis)<a href="https://agentmods.dev/skills/hoanghaoha/survy-agent-skills/survey-analysis"><img src="https://agentmods.dev/badge/skills/hoanghaoha/survy-agent-skills/survey-analysis/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/hoanghaoha/survy-agent-skills/survey-analysis"><img src="https://agentmods.dev/badge/skills/hoanghaoha/survy-agent-skills/survey-analysis.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 | $0.00210 | $0.05033 |
| Opus 5.5 | $0.00084 | $0.02013 |
| Sonnet 5.5 | $0.00042 | $0.01007 |
| Haiku 4.5 | $0.00021 | $0.00503 |
Grade A, and why
survey-analysis 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 2mo 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 — 519 lines — stays where its author put it; the contents beside it link to each section on GitHub.
survy — Survey Data Analysis Skill
survy is a lightweight Python library for processing, transforming, and analyzing survey data.
Its central design principle is treating survey constructs — especially multiselect questions — as
first-class concepts rather than awkward DataFrame workarounds.
Install: Always install the latest version — pip install --upgrade survy
Powered by: Polars (all DataFrames returned are Polars, not pandas)
1. Core Objects
Survey
Top-level container. Created via read_* functions — never instantiate directly.
Access variables with survey["Q1"]. Print for a compact summary.
Variable
Wraps a single Polars Series plus survey metadata. Key attributes:
| Attribute | Type | Description |
|---|---|---|
id |
str |
Column name (read/write via property) |
label |
str |
Human-readable label (read/write); defaults to id if unset |
vtype |
VarType |
One of VarType.SELECT, VarType.MULTISELECT, VarType.NUMBER |
value_indices |
dict[str, int] |
Answer code → numeric index mapping; always empty {} for NUMBER |
base |
int |
Count of non-null/non-empty responses |
len |
int |
Total row count including nulls |
dtype |
polars.DataType |
Underlying Polars dtype |
frequencies |
polars.DataFrame |
Frequency table (value, count, proportion) |
sps |
str |
SPSS syntax for this variable |
2. Reading Data
All readers return a Survey object. The key challenge survy
solves at read time is recognizing multiselect questions —
questions where one respondent can choose multiple answers.
Raw data encodes these in two very different layouts, and survy
needs to know which layout it's looking at so it can merge the
data into a single logical variable.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 519 lines · 210 tokens per session scan A 09e53bdc5b0e
survey-analysis is a skill published in the GitHub repository hoanghaoha/survy-agent-skills (2 stars, last pushed 6mo ago), licensed MIT. It adds 210 tokens to every session and 5,033 once invoked, about $0.0008 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.
survey-analysis compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| survey-analysishoanghaoha/survy-agent-skills | Skill | 2 | 6mo ago | MIT | A | 210 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |