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.
npx skills add PlamenTSV/plamen --skill peer-scoring-correctnessgit clone --depth 1 https://github.com/PlamenTSV/plamenWrote 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/plamentsv/plamen/peer-scoring-correctness)<a href="https://agentmods.dev/skills/plamentsv/plamen/peer-scoring-correctness"><img src="https://agentmods.dev/badge/skills/plamentsv/plamen/peer-scoring-correctness/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.
<a href="https://agentmods.dev/skills/plamentsv/plamen/peer-scoring-correctness"><img src="https://agentmods.dev/badge/skills/plamentsv/plamen/peer-scoring-correctness.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00027 | $0.00967 |
| Opus 5 | $0.00014 | $0.00483 |
| Sonnet 5 | $0.00005 | $0.00193 |
| Haiku 4.5 | $0.00003 | $0.00097 |
Grade A, and why
peer-scoring-correctness 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 6d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Injectable Skill: Peer Scoring Correctness
L1 trigger:
P2Pflag AND (score_peer,peer_score,reputation,misbehavior,ban_peer,peer_scoringdetected) Inject Into:depth-network-surfaceLanguage: Go and Rust Finding prefix:[PSC-N]
1. Reward / Penalty Symmetry
Enumerate all score increments and all score decrements. For every reward path, identify the matching penalty path and ask whether a malicious peer can gain trust faster than it can lose it.
Tag: [PEER-SCORE:SYMMETRY]
Required full-leg matrix: Do not stop after the first scoring bug. Build a complete table of every score mutation and every peer-performance observation:
| Leg | Event / endpoint | Reward? | Penalty? | Error classes penalized | Can attacker farm? |
|---|---|---|---|---|---|
| block validation | valid / invalid block | ||||
| block pool / orphan handling | unknown parent, invalid data, timeout | ||||
| health check | HTTP 200, non-200, timeout, parse error | ||||
| data/chunk request | delivery success, delivery fail, no response | ||||
| gossip | valid message, invalid message, duplicate, re-gossip | ||||
| bootstrap / peer list | useful peer, bogus peer, stale address |
Every blank Penalty? for a harmful event is a candidate finding. Every blank
Can attacker farm? for a reward event is incomplete analysis.
2. Penalty Coverage
Build a failure-mode table and verify every harmful action has a score impact:
| Failure mode | Penalized? | Immediate? | Resettable? |
|---|---|---|---|
| Invalid block / tx | |||
| Timeout / stall | |||
| Malformed gossip | |||
| Health-check failure | |||
| Excessive requests | |||
| Non-response / timeout | |||
| Non-200 HTTP response | |||
| Delivery failure after accepted request | |||
| Invalid block held in cache / orphan pool | |||
| Stale peer address update |
Tag: [PEER-SCORE:COVERAGE]
3. Farming / Free-Riding
Check whether peers can cheaply farm score via ping loops, get_data style
requests, acknowledgements without contribution, or reconnect-based resets.
Quantify attacker cost versus defender work.
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.
- 6d ago First seen · 103 lines · 27 tokens per session scan A 834f038e5b67
peer-scoring-correctness is a skill published in the GitHub repository PlamenTSV/plamen (295 stars, last pushed 2d ago), licensed MIT. It adds 27 tokens to every session and 967 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 2026-09-03.
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