opensession: Skill for Claude Code

.agents/skills/pstack-suite/skills/show-me-your-work/SKILL.md

show-me-your-work is a skill for Claude Code from tellahq/opensession. It costs 77 tokens per session (1,600 once invoked), scanned A, original, MIT.

A decision log format for long-running or unattended work. It records each important choice, the reason for it, the evidence behind it, and the resulting state in a tab-separated file.

In plain words
What is it for?
It helps document multi-phase runs, migrations, reviews, experiments, and other work where someone needs to verify how decisions were made.
Why use it?
It gives reviewers a concise trail they can inspect later without rereading the entire conversation or repeating the work.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: installed under .agents/ (shared by several agents).

This is tellahq/opensession's own configuration. It tells Claude Code how to work on opensession itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything opensession configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/tellahq/opensession/main/.agents/skills/pstack-suite/skills/show-me-your-work/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/tellahq/opensession

Made for: Claude Code.

Wrote 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.

agentmods badge for show-me-your-work

README.md
[![agentmods](https://agentmods.dev/badge/skills/tellahq/opensession/show-me-your-work.svg)](https://agentmods.dev/skills/tellahq/opensession/show-me-your-work)
Your own site
<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>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,600 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 3d ago against content hash 0b8806bc7686, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/log.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/pstack-suite/skills/show-me-your-work/SKILL.md · 83 lines

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

Read the full file on GitHub · 83 lines

Files

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.

Changes

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.

  1. 3d ago First seen · 83 lines · 77 tokens per session scan A 0b8806bc7686

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

recipe-create-meet-space

Create a Google Meet meeting space and share the join link.

googleworkspace/cli · 18 tokens

atmos-config

Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.

cloudposse/atmos · 31 tokens

workthreads

SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…

specstoryai/getspecstory · 126 tokens

story-readiness

Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is…

Donchitos/Claude-Code-Game-Studios · 77 tokens

autotask-creator

Rules for automation CRUD from the group-chat commander. The commander does not call mutation tools and does not edit cloud/autotasks files directly. It emits one or more top-level ... containers in its final text; the bus parses and applies them after the turn.

Orkas-AI/Orkas · 5 tokens

monorepo-management

Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.

wshobson/agents · 54 tokens