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 glebis/claude-skills --skill synthetic-session-generatorgit clone --depth 1 https://github.com/glebis/claude-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/glebis/claude-skills/synthetic-session-generator)<a href="https://agentmods.dev/skills/glebis/claude-skills/synthetic-session-generator"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/synthetic-session-generator/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/glebis/claude-skills/synthetic-session-generator"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/synthetic-session-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00150 | $0.02676 |
| Opus 5 | $0.00075 | $0.01338 |
| Sonnet 5 | $0.00030 | $0.00535 |
| Haiku 4.5 | $0.00015 | $0.00268 |
Grade A, and why
synthetic-session-generator 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 8d 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 — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Synthetic Session Generator
Purpose
Generate fictional but believable coaching/therapy session transcripts that read like real recorded sessions, while remaining clearly synthetic. Outputs feed three jobs: eval datasets (with ground-truth labels to benchmark summarizers and analyzers), product demos (realistic sessions without exposing real client data), and training/prompt examples (few-shot material for a coaching or therapy assistant).
Realism comes from two disciplines: persona consistency (a client speaks the same way, carries the same history and presenting issues across a session arc) and modality fidelity (the practitioner uses the techniques, question forms, and pacing of the chosen framework). Every output is watermarked as synthetic so it can never be mistaken for a real clinical record.
When to Use
Use when a user asks for fake/synthetic/mock/demo coaching or therapy transcripts, eval or test data
for session-analysis tools (e.g. the coaching-session-summarizer), few-shot dialogue examples, or
persona-consistent session series. Do not use to analyze or summarize a real transcript — that
is the job of coaching-session-summarizer or transcript-analyzer.
Workflow
Step 0 — Setup mode (configure defaults)
When the user wants to configure the skill ("setup", "set my defaults", "always use Russian / IFS / 50-minute sessions"), run setup mode. Offer the three choices via AskUserQuestion, then persist them:
- Language — output language for the transcript (
en,ru,de,es,fr,pt,it,nl). - Modality — default framework (
icf-grow,cbt,ifs,act-mi). - Session duration — minutes (e.g. 25 / 50 / 80); mapped to a turn budget (~0.6 turns/min).
python3 scripts/setup_config.py --language ru --modality cbt --duration 50 --show
python3 scripts/setup_config.py --show # view current defaults
This writes config.json in the skill directory. Later scaffold_session.py runs inherit these
defaults, so the user only specifies what differs (e.g. persona and session position). Per-run flags
always override the saved config.
What ships with it
14 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.
- assets/templates/example_fathom.txt 983 B
- assets/templates/example_markdown.md 1.1 KB
- assets/templates/example_plain.md 933 B
- assets/templates/example_session.json 3.4 KB
- README.md 3.8 KB
- references/modalities.md 4.3 KB
- references/personas.md 3.0 KB
- references/realism_guide.md 2.5 KB
- screenshot.png 355 KB
- scripts/_common.py 7.4 KB runs code
- scripts/convert_format.py 4.4 KB runs code
- scripts/make_card.py 7.1 KB runs code
- scripts/scaffold_session.py 5.6 KB runs code
- scripts/setup_config.py 2.5 KB runs code
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.
- 8d ago First seen · 186 lines · 150 tokens per session scan A 0aa52aab8360
synthetic-session-generator is a skill published in the GitHub repository glebis/claude-skills (375 stars, last pushed 10d ago), licensed MIT. It adds 150 tokens to every session and 2,676 once invoked, about $0.0007 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 2026-09-03.
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