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/show-me-your-work/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/show-me-your-work)<a href="https://agentmods.dev/skills/tellahq/opensession/show-me-your-work"><img src="https://agentmods.dev/badge/skills/tellahq/opensession/show-me-your-work.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 51 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00077 | $0.01600 |
| Opus 5 | $0.00039 | $0.00800 |
| Sonnet 5 | $0.00015 | $0.00320 |
| Haiku 4.5 | $0.00008 | $0.00160 |
Grade A, and why
show-me-your-work scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Show me your work
For work a human reviews after the fact, a decision trail lets them reconstruct what was decided, why, and on what evidence, without rerunning the work or reading the whole transcript. Keep one canonical log so the trail is consistent and a future agent can find it.
The format
A single TSV file, one row per decision. TSV because GitHub renders it as a sortable table, column -s$'\t' -t and spreadsheets read it, and a row appends with one command. Cells stay single-line. Evidence is a pointer, not prose.
Copy references/decision-log-template.tsv (the header row) to start a clean log. Columns:
- ts. ISO8601 timestamp. The timeline axis.
- phase. The phase or workstream.
- decision. What was chosen or done, one line.
- why. The reason in plain words. If a principle drove it, say it plainly (
explored options first, this was a one-way door), not as a jargon tag. - evidence. A link or path that proves it: commit SHA, PR number,
file:line, or an artifact, trace, or screenshot path. Never a paragraph. - result. The outcome or predicate state:
tests green,reverted,pixel-diff 0,INCONCLUSIVE,open.
An example, plain-spoken so a reviewer reads it at a glance. This is illustration only; don't copy these rows into a real log.
ts phase decision why evidence result
2026-05-24T09:02:00Z frame counted the work first, about 100 components and roughly 75 hours wanted to know the size before starting a long run commit 3a9f1c2 found 5 things to sort out before starting
2026-05-24T09:40:00Z harness took screenshots of the old version before changing anything so we can compare old against new and catch any visual change scripts/snapshot.sh, baseline/ saved 120 reference screenshots
2026-05-24T11:15:00Z widget moved the widget styles over without changing how it looks keep the change small and the result identical commit 7c21e0a, pixel-diff 0 looks identical, tests pass
2026-05-24T12:30:00Z widget threw out a helper's work because its screenshots were blank checked the real files instead of trusting its summary candidate workspace discarded, tightened the instructions for next time
What ships with it
2 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 · 83 lines · 77 tokens per session scan A 0b8806bc7686
show-me-your-work is a skill published in the GitHub repository tellahq/opensession (357 stars, last pushed today), licensed MIT. It adds 77 tokens to every session and 1,600 once invoked, about $0.0004 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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