Mark

Report Feedback

report_feedback

Records what the person asked you to change while drafting, and your own checks on the draft, so Mark can later suggest brand rules. Each call stores one new report. Call it at two moments: when the person states a standing rule ("never say game-changer"), before you ask whether to save it; and once on the version they accept, after save_post, with that postId. For a piece that lives outside Mark, pass externalRef instead. Each iteration is one ask: a short paraphrase in ask, its category, and scope (tenant_wide when they said it applies to everything, this_piece when only here, unsure otherwise; never guess). before, after and userQuote are optional short excerpts of the changed words and of what the person said. Keep every excerpt short, and never paste the conversation or a full draft. selfChecks list the checks you ran (check, result pass/warn/fail, reason). Recording feedback changes no rule. When the person agrees a rule, save it with save_content_exclusion (pass this report's id as feedbackId) for a phrase Mark should block or warn on, or update_brand_profile for voice guidance. Asks scoped tenant_wide or unsure come back as suggested rules from suggest_brand_rules. Related: save_content_exclusion, update_brand_profile, save_post, suggest_brand_rules.

Input Schema

TableJSON Schema

Name	Required	Description
`notes`	No	Anything else worth keeping, at most 1,000 characters. Not the conversation.
`postId`	No	The saved post this report is about, from save_post.
`channel`	Yes	The channel being drafted.
`iterations`	No	Up to 20 asks: {ask, category, before?, after?, userQuote?, scope}. Each text at most 300 characters.
`selfChecks`	No	Up to 20 checks you ran: {check (at most 80 characters), result, reason (at most 300)}.
`externalRef`	No	Link to a piece outside Mark, at most 2,048 characters.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 20, 2026

changedInput schema / properties / channel / enum

Previous value: -[
-  "instagram",
-  "facebook",
-  "youtube",
-  "pinterest",
-  "tiktok",
-  "x",
-  "linkedin",
-  "blog",
-  "faq",
-  "competitor_page",
-  "landing_page",
-  "email",
-  "meta_ads",
-  "google_ads"
-]New value: +[
+  "instagram",
+  "facebook",
+  "youtube",
+  "pinterest",
+  "tiktok",
+  "x",
+  "linkedin",
+  "linkedin_article",
+  "blog",
+  "faq",
+  "competitor_page",
+  "landing_page",
+  "email",
+  "meta_ads",
+  "google_ads"
+]

AddedOct 15, 2026

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare the write/non-idempotent/non-destructive profile; the description adds the decisive context that each call appends one new report and that 'Recording feedback changes no rule', so the agent knows the side effect is scoped to storage. It also sets privacy constraints (keep excerpts short, never paste the conversation or a full draft).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Dense but front-loaded: the core action and the two invocation moments come first, with constraints and sibling routing after. The trailing 'Related:' line partly repeats tools already named in the body, which is the only redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 6-parameter tool with nested arrays and an existing output schema, the description covers purpose, timing, parameter intent, privacy limits and the follow-up workflow. Return values need not be explained since an output schema exists, and nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% so the baseline is 3, but the description goes beyond it by explaining scope semantics (tenant_wide vs this_piece vs unsure, 'never guess') and characterizing before/after/userQuote as optional short excerpts. The nested-array structure is echoed but the enum guidance is the real added value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (records/stores) and resource (a feedback report of asks and self-checks), plus the downstream purpose (so Mark can suggest brand rules). It distinguishes itself from siblings by naming save_content_exclusion, update_brand_profile, save_post and suggest_brand_rules.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit invocation moments (when a standing rule is stated, before asking to save; once on the accepted version after save_post with that postId), an alternative for out-of-Mark pieces via externalRef, and clearly routes rule-saving to save_content_exclusion/update_brand_profile rather than this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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