Borrowing it
Nothing to install: this file belongs to tellahq/opensession. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tellahq/opensession/main/.agents/skills/pstack-suite/skills/reflect/SKILL.mdgit clone --depth 1 https://github.com/tellahq/opensessionWrote 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/tellahq/opensession/reflect)<a href="https://agentmods.dev/skills/tellahq/opensession/reflect"><img src="https://agentmods.dev/badge/skills/tellahq/opensession/reflect.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.00932 |
| Opus 5 | $0.00018 | $0.00466 |
| Sonnet 5 | $0.00007 | $0.00186 |
| Haiku 4.5 | $0.00004 | $0.00093 |
Grade A, and why
reflect 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 3d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reflect
Mine the current conversation for durable learnings, then route them into skill edits.
When to invoke
- The user said "reflect" or "/reflect".
- A complex task (5+ tool calls) just landed cleanly and the recipe is worth keeping.
- The agent hit dead ends, found the working path, and the path generalizes.
- The user corrected the agent's approach mid-task.
- A non-trivial workflow emerged that isn't captured anywhere.
Skip when the conversation is trivial, off-topic, or already covered by an existing skill the parent followed correctly. One-offs are not learnings.
Process
1. Locate the active transcript
Use the current conversation context for the active session. For an earlier session, discover the policy-gated Open Session session and history tools, identify it by exact id and explicit creator, and read only the relevant transcript windows. Never scan transcript files, databases, or global session storage. If no gated transcript resolves, write a tight digest of the current session and pass that instead.
2. Spawn three reviewers in parallel
Spawn three ask-mode child sessions in parallel with self-contained /pstack briefs that forbid file writes. Reviewers may use MCPs available to their Open Session session for cited context lookups. The parent applies edits.
| Lens | Model | Prompt template |
|---|---|---|
| Judgment | configured supporting model when available, otherwise inherited | references/judgment-reviewer.md |
| Tooling | configured supporting model when available, otherwise inherited | references/tooling-reviewer.md |
| Divergent | a different configured family when available, otherwise inherited | references/divergent-reviewer.md |
Pass each template verbatim with a reduced transcript digest and, only when needed, an exact policy-gated session id. Reviewers return findings in their reports.
3. Synthesize
Spawn one ask-mode /pstack child as the synthesizer. It may use its policy-gated MCPs to spot-check citations. Use references/synthesizer.md verbatim, with each reviewer's full output inlined where marked. The synthesizer returns a structured Accepted / Rejected / Backlog list.
What ships with it
4 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.
- 3d ago First seen · 70 lines · 36 tokens per session scan A 2ec0672aa6ee
reflect is a skill published in the GitHub repository tellahq/opensession (357 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 932 once invoked, about $0.0002 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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