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wrap-up

wrap-up is a skill for Claude Code from samkawsarani/sams-product-plugins. It costs 62 tokens per session (674 once invoked), scanned A, original, MIT.

A session wrap-up workflow that records useful learnings, updates tracked hypotheses, and preserves knowledge for later sessions. It is triggered by phrases such as “done” or “wrap up.”

In plain words
What is it for?
Use it at the end of work to review affected domains, update supporting or contradicting evidence, identify new facts, and propose—but not automatically approve—knowledge updates.
Why use it?
It reduces the chance that decisions, evidence, or lessons from a session are forgotten. It also keeps uncertain ideas separate from confirmed knowledge.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter; mentions AGENTS.md.

Part of the wrap-up plugin — 1 skill shipped together

not rated 2repo 1mo ago A scan 62 tokens original MIT

Good fit Use it at the end of work to review affected domains, update supporting or contradicting evidence, identify new facts, and propose—but not automatically approve—knowledge updates.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/samkawsarani/sams-product-plugins/wrap-up
View source ↗ samkawsarani/sams-product-plugins
Install

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.

Any agent
npx skills add samkawsarani/sams-product-plugins --skill wrap-up
Clone the repo
git clone --depth 1 https://github.com/samkawsarani/sams-product-plugins

Made for: Claude Code.

Or install wrap-up, the plugin that ships this one along with the rest of its 1 skill.

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 wrap-up

README.md
[![agentmods](https://agentmods.dev/badge/skills/samkawsarani/sams-product-plugins/wrap-up/github.svg)](https://agentmods.dev/skills/samkawsarani/sams-product-plugins/wrap-up)
Your own site
<a href="https://agentmods.dev/skills/samkawsarani/sams-product-plugins/wrap-up"><img src="https://agentmods.dev/badge/skills/samkawsarani/sams-product-plugins/wrap-up/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.

agentmods 80×15 button for wrap-up

Your own site · 80×15
<a href="https://agentmods.dev/skills/samkawsarani/sams-product-plugins/wrap-up"><img src="https://agentmods.dev/badge/skills/samkawsarani/sams-product-plugins/wrap-up.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 674 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.
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 $0.00062 $0.00674
Opus 5.5 $0.00025 $0.00270
Sonnet 5.5 $0.00012 $0.00135
Haiku 4.5 $0.00006 $0.00067

Measured 2mo ago against content hash 8a586d99f6f7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

wrap-up 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.

plugins/wrap-up/skills/wrap-up/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Your Task

Run the session wrap-up for this product OS workspace. Takes 2-3 minutes. Ensures learnings persist.

Announce at start: "Running wrap-up."

Step 1: Identify touched domains

Based on this session's work, identify which domains under knowledge/domains/ were relevant. If unclear, infer from session context. List the domains identified before proceeding.

Step 2: Hypothesis scan

For each touched domain, read hypotheses.md. For each non-retired hypothesis:

  • Confirming evidence this session? → Increment Confirmations count, add inline dated note: *(YYYY-MM-DD: [source/reason])*
  • Contradicting evidence? → Increment Contradictions count, add inline dated note
  • 3+ confirmations? → Surface to Sam: "H[N] in [domain] has 3 confirmations. Proposed move to knowledge.md: [draft text]. Approve?"

Never auto-promote. Sam approves all promotions.

Step 3: New knowledge

Did this session surface new confirmed facts or rules not already in knowledge.md?

Rule of thumb — fact vs hypothesis: If it requires future validation to know if it's true, it's a hypothesis (goes to hypotheses.md). If it's already evidenced in this session — a decision was made, a number was stated, a process was confirmed — it's a fact (goes to knowledge.md).

  • New fact → append under ## What we know (facts) with *(added YYYY-MM-DD)* tag if time-sensitive
  • New confirmed rule → append under ## Rules (apply by default) with Confirmed by + Apply when
  • Cross-domain rule? → Check if it belongs in knowledge/domains/shared.md instead

Step 4: Corrections

Did Sam correct the agent on anything this session?

  • Agent behavior correction → update relevant AGENTS.md (root or knowledge/) with the corrected behavior
  • Domain fact correction → update the relevant knowledge.md entry
  • Fact about Sam → update knowledge/about-me/about-me.md

Step 5: Housekeeping

  • Update *Last updated: YYYY-MM-DD* header on any modified files
  • Flag (don't fix) any domain where *Last updated:* is older than 90 days: "Note: [domain]/knowledge.md last updated YYYY-MM-DD — may be worth a review"

Read the full file on GitHub · 71 lines

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. 2mo ago First seen · 71 lines · 62 tokens per session scan A 8a586d99f6f7

Subscribe to this mod's changes

wrap-up is a skill published in the GitHub repository samkawsarani/sams-product-plugins (2 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 674 once invoked, about $0.0002 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.

Memory and context
Related

wrap-up compared with skills from other repositories

wrap-up next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
wrap-upsamkawsarani/sams-product-pluginsSkill21mo agoMITA62Claude Code
knowledge-ingestopenclaw/openclawSkill394ktodayMITA80Claude Code, Codex
mem0-oss-to-platformmem0ai/mem0Skill69kyesterdayApache-2.0A217Claude Code, Codex
forgetasgeirtj/system_prompts_leaksSkill71kyesterdayCC0-1.0A0Claude Code, Codex
Cortexdanielmiessler/LifeOSSkill20k2d agoMITA184Claude Code
ha-data-storesshiwenwen/hope-agentSkill1.9ktodayMITA115Claude Code, Codex
memoryopensquilla/opensquillaSkill7.1k7d agoApache-2.0A44Claude Code, Codex