share-allocation-fairness

share-allocation-fairness is a skill for Claude Code, Codex from PlamenTSV/plamen. It costs 26 tokens per session (2,013 once invoked), scanned A, original, MIT.

A fairness review guide for systems that give users shares or tokens based on deposits, contributions, or participation. It examines pro-rata, time-weighted, queue-based, and epoch-based allocation designs.

In plain words
What is it for?
Auditing staking, reward, liquidity, investment, and other share-allocation mechanisms built with Aptos Move assets.
Why use it?
It helps find advantages caused by deposit timing, queue manipulation, missing time weighting, or dilution of earlier participants.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Auditing staking, reward, liquidity, investment, and other share-allocation mechanisms built with Aptos Move assets.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/plamentsv/plamen/share-allocation-fairness
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 PlamenTSV/plamen --skill share-allocation-fairness
Clone the repo
git clone --depth 1 https://github.com/PlamenTSV/plamen

Made for: Claude Code, Codex.

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 share-allocation-fairness

README.md
[![agentmods](https://agentmods.dev/badge/skills/plamentsv/plamen/share-allocation-fairness.svg)](https://agentmods.dev/skills/plamentsv/plamen/share-allocation-fairness)
Your own site
<a href="https://agentmods.dev/skills/plamentsv/plamen/share-allocation-fairness"><img src="https://agentmods.dev/badge/skills/plamentsv/plamen/share-allocation-fairness.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,013 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 pass 7 Sept 2026
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 $0.00026 $0.02013
Opus 5 $0.00013 $0.01007
Sonnet 5 $0.00005 $0.00403
Haiku 4.5 $0.00003 $0.00201

Measured 8d ago against content hash 5a75310d052c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

share-allocation-fairness 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.

agents/skills/aptos/share-allocation-fairness/SKILL.md · 163 lines

How it starts

The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: SHARE_ALLOCATION_FAIRNESS

Trigger: SHARE_ALLOCATION flag detected in pattern scan Used by: Breadth agents, depth-edge-case

Purpose

Analyze fairness of share/token allocation mechanisms where users receive shares proportional to deposits, contributions, or participation -- checking for late-entry advantages, queue-position gaming, and time-weighting omissions. Adapted for Aptos Move FungibleAsset-based accounting and resource model.

Methodology

STEP 1: Classify Allocation Mechanism

Identify which pattern the protocol uses:

Type Pattern Key Risk
Pro-rata snapshot Shares minted at fixed ratio at deposit time Late depositors dilute early depositors accrued value
Time-weighted Shares accrue value based on duration held Checkpoint manipulation, discrete vs continuous accrual
Queue-based Deposits processed in batch/queue order Queue position gaming, front-running batch processing
Epoch-based Shares valued per epoch/period boundary Cross-epoch timing arbitrage

Aptos-specific: Identify whether shares are represented as:

  • FungibleAsset with custom metadata (standard FA shares)
  • Coin<ShareType> (legacy coin shares)
  • Custom resource with balance field (non-standard)
  • Object<T> with proportional ownership (object-based shares)

STEP 2: Late Entry Attack Model

For each allocation entry point:

  1. Identify accrual source: What generates value for existing share holders? (yield, fees, rewards, appreciation)
  2. Trace timing: When does accrued value become claimable vs when can new shares enter?
  3. Check for time-weighting: Does allocation account for HOW LONG shares were held, or only THAT shares are held?
  4. Model attack: Can a depositor enter AFTER value accrues but BEFORE distribution, capturing value they did not earn?
Entry Function Accrual Source Time-Weighted? Late Entry Possible? Impact

Read the full file on GitHub · 163 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. 8d ago First seen · 163 lines · 26 tokens per session scan A 5a75310d052c

Subscribe to this mod's changes

share-allocation-fairness is a skill published in the GitHub repository PlamenTSV/plamen (286 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 2,013 once invoked, about $0.0001 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 2026-08-30.

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