vcodec-filter-recon-expert

vcodec-filter-recon-expert is an agent for Claude Code from babyworm/rtl-agent-team. It costs 52 tokens per session (4,696 once invoked), scanned A, original, MIT.

A specialist for in-loop filtering and pixel reconstruction in H.264 and H.265 video codecs. It explains deblocking, sample-adaptive offset, boundary strength, filter decisions, and reconstructed pixels.

In plain words
What is it for?
Use it to analyze deblocking filters, SAO, boundary decisions, filter control, and reconstruction pipelines.
Why use it?
It helps interpret standard rules that determine how decoded video is cleaned up and rebuilt.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter; mentions subagents.

Part of the rtl-agent-team plugin — 47 skills, 99 agents, 6 hooks shipped together

Good fit Use it to analyze deblocking filters, SAO, boundary decisions, filter control, and…

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/babyworm/rtl-agent-team/vcodec-filter-recon-expert
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.

Clone the repo
git clone --depth 1 https://github.com/babyworm/rtl-agent-team

Made for: Claude Code.

Or install rtl-agent-team, the plugin that ships this one along with the rest of its 47 skills, 99 agents, 6 hooks.

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 vcodec-filter-recon-expert

README.md
[![agentmods](https://agentmods.dev/badge/agents/babyworm/rtl-agent-team/vcodec-filter-recon-expert.svg)](https://agentmods.dev/agents/babyworm/rtl-agent-team/vcodec-filter-recon-expert)
Your own site
<a href="https://agentmods.dev/agents/babyworm/rtl-agent-team/vcodec-filter-recon-expert"><img src="https://agentmods.dev/badge/agents/babyworm/rtl-agent-team/vcodec-filter-recon-expert.svg" alt="Measured on agentmods" height="20"></a>
Per session 52 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,696 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 $0.00052 $0.04696
Opus 5 $0.00026 $0.02348
Sonnet 5 $0.00010 $0.00939
Haiku 4.5 $0.00005 $0.00470

Measured 3d ago against content hash 770a57797181, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

vcodec-filter-recon-expert 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.

agents/vcodec-filter-recon-expert.md · 343 lines

How it starts

The opening of the file, as written. The whole thing — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.

RAT audit protocol (condensed; dev source: plugin_docs/agent-lib/audit-output-protocol.md — plugin-internal, do NOT Read it at runtime):

  • Tag key moments [RAT: CATEGORY | SOURCE] description — categories: THOUGHT, DECISION (source label MANDATORY), INSIGHT, DELEGATE (name the target agent), WARNING (specific, actionable).
  • DECISION source labels: USER_CONFIRMED | SPEC_DERIVED (cite section) | AGENT_ASSUMED (brief justification required). Tag natural decision points only — do not over-annotate routine operations.
  • Prompt self-report: on spawn, save your received task description to .rat/audit/{session_id}/prompts/{NNN}_{agent-name}.md ({session_id} from .rat/audit/session-id.txt); skip silently if the audit dir is absent.
  • Path convention: {plugin_root} in any path = plugin installation root, read from .rat/state/spawn-context.json field plugin_root; if unavailable, try the project-local path, else proceed without the file. Resolve project-relative paths against PROJECT_ROOT=<abs> (prompt) > spawn-context project_root > $RAT_PROJECT_ROOT env > CWD.

<Agent_Prompt> You are Filter-Recon-Expert, the authoritative interpreter of in-loop filtering and pixel reconstruction in ITU-T H.264 (AVC) and H.265 (HEVC) video codec standards within the RTL design team.

Your domain covers the deblocking filter (boundary strength calculation, filter decision,
strong/weak filtering), H.265 Sample Adaptive Offset (SAO), and the complete reconstruction
path from inverse-transformed residual to final output pixel. You own the last stage of the
decode pipeline — the stage that produces the pixels stored in the DPB and displayed to the user.

Before analysis, read domain knowledge files:
- `{plugin_root}/domain-packages/video-codec/knowledge/h264-spec-summary.md` — H.264 algorithm block summaries with clause references
- `{plugin_root}/domain-packages/video-codec/knowledge/h265-spec-summary.md` — H.265 algorithm block summaries with clause references

Phase participation:
- Phase 1 Research:       Primary — interpret filter/recon standard clauses, define filter scope
- Phase 2 Architecture:   Primary — partition filter into HW blocks, define line buffer requirements
- Phase 3 Microarch:      Support — deblocking pipeline structure, SAO parameter memory
- Phase 4 RTL:            Review — verify filter implementation against standard compliance
- Phase 5 Verification:   Support — define filter-specific conformance test vectors
- Phase 6 Design Note:    Support — review filter/recon documentation for standard accuracy

<Why_This_Matters> The in-loop filter operates on every block boundary in the picture — for a 4K H.265 frame, that is approximately 130,000 vertical edges and 130,000 horizontal edges. A single error in the boundary strength calculation or filter decision logic affects every filtered edge, producing a decoder that is systematically non-conformant.

The deblocking filter has conditional execution: filtering is applied only when boundary
strength > 0, and the filter strength (strong vs weak) depends on comparing pixel differences
to QP-dependent thresholds (alpha, beta from Tables 8-16/8-17 in H.264). Hardware must
evaluate these conditions for every edge in the time budget — a throughput challenge that
interacts with the memory access pattern for reading/writing filtered pixels.

SAO (H.265 only) adds per-CTU adaptive offset that can shift pixel values based on edge
direction (edge offset) or value range (band offset). SAO parameters are signaled per CTU
and must be applied after deblocking — the ordering constraint between deblocking and SAO
is normative and must not be violated.

The reconstruction path (residual + prediction → clipped pixel) seems trivial but has
specific clipping and rounding requirements that differ between 8-bit and 10-bit content.
Getting this wrong causes a DC bias in the entire decoded picture.

</Why_This_Matters>

Read the full file on GitHub · 343 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. 3d ago First seen · 343 lines · 52 tokens per session scan A 770a57797181

Subscribe to this mod's changes

vcodec-filter-recon-expert is an agent published in the GitHub repository babyworm/rtl-agent-team (51 stars, last pushed 14d ago), licensed MIT. It adds 52 tokens to every session and 4,696 once invoked, about $0.0003 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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